
"""

INPUT: 
-> Data train

PROCESS:
-> variance threshold (save selected feature names into pickle)
-> Standard Scaling (save scaler into pickle)
-> Genetic Algorithm Features Selection (save result into pickle)

OUTPUT:
-> selected_features_statistical.pkl (list)
-> scaler.pkl (scaler)
-> selected_features_GA.pkl (dictionary)

"""

'\n\nINPUT: \n-> Data train\n\nPROCESS:\n-> variance threshold (save selected feature names into pickle)\n-> Standard Scaling (save scaler into pickle)\n-> Genetic Algorithm Features Selection (save result into pickle)\n\nOUTPUT:\n-> selected_features_statistical.pkl (list)\n-> scaler.pkl (scaler)\n-> selected_features_GA.pkl (dictionary)\n\n'


import pandas as pd
import numpy as np
import joblib


### Load Train set
train = pd.read_csv('D:\Coding\Machine Learning\Bioinformatics\QSAR study on falcipain inhibitor\Dataset Falcipain\Train.csv')
train


X_train = train.iloc[:,:-1]
y_train = train.iloc[:, [-1]]


### Load Test set
test = pd.read_csv('D:\Coding\Machine Learning\Bioinformatics\QSAR study on falcipain inhibitor\Dataset Falcipain\Test.csv')
test


X_test = test.iloc[:,:-1]
y_test = test.iloc[:, [-1]]


features_name = X_train.columns.to_list()


from sklearn.feature_selection import VarianceThreshold


selector = VarianceThreshold(threshold=0.5)
selector.fit_transform(X_train)

### Total number of features after variance threshold

len(selector.get_feature_names_out(features_name))

564


### save and export selected features to pickle
selected_features_statistical = selector.get_feature_names_out(features_name)
joblib.dump(selected_features_statistical, 'Dataset Falcipain\selected_features_statistical.pkl')

['Dataset Falcipain\\selected_features_statistical.pkl']


X_train[selected_features_statistical]


# Standarization
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()

# Train
X_train_scaled = scaler.fit_transform(X_train)
X_train_scaled = pd.DataFrame(X_train_scaled, columns=features_name)
X_train_scaled.to_csv('Dataset Falcipain/x_train_scaled.csv')
y_train.to_csv('Dataset Falcipain/y_train.csv')

# Test
X_test_scaled = scaler.transform(X_test)
X_test_scaled = pd.DataFrame(X_test_scaled, columns=features_name)
X_test_scaled.to_csv('Dataset Falcipain/x_test_scaled.csv')
y_test.to_csv('Dataset Falcipain/y_test.csv')

### Save the scaler for transform the test sets later on (if needed)
joblib.dump(scaler, 'Dataset Falcipain/scaler.pkl')

['Dataset Falcipain/scaler.pkl']


X_train_scaled[selected_features_statistical]


X_test_scaled[selected_features_statistical]


### Setting up Global Weight Score
weight_score_global = 0.8


"""

Zoofs library dependencies

"""
import plotly.graph_objects as go
from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
import logging as log
import scipy
import colorlog
import logging



class BaseOptimizationAlgorithm(ABC):

    def __init__(self,
                 objective_function,
                 n_iteration: int = 1000,
                 timeout: int = None,
                 population_size=50,
                 minimize=True,
                 logger=None,
                 **kwargs):
        self.kwargs=kwargs
        self.objective_function = objective_function
        self.minimize = minimize
        self.population_size = population_size
        self.n_iteration = n_iteration
        self.timeout = timeout
        self.my_logger=logger

    @abstractmethod
    def fit(self):
        pass

    def sigmoid(self, x):
        return 1/(1+np.exp(-x))

    def _evaluate_fitness(self, model, x_train, y_train, x_valid, y_valid, particle_swarm_flag=0,dragon_fly_flag=0):
        scores = []
        for i, individual in enumerate(self.individuals):
            chosen_features = [index for index in range(
                x_train.shape[1]) if individual[index] == 1]
            x_train_copy = x_train.iloc[:, chosen_features]
            x_valid_copy = x_valid.iloc[:, chosen_features]

            feature_hash = '_*_'.join(
                sorted(self.feature_list[chosen_features]))
            if feature_hash in self.feature_score_hash.keys():
                score = self.feature_score_hash[feature_hash]
            else:
                score = self.objective_function(
                    model, x_train_copy, y_train, x_valid_copy, y_valid, **self.kwargs)
                if not(self.minimize):
                    score = -score
#Adding Feature Weight
                weight_score = weight_score_global
                total_feat = X_train[selected_features_statistical].shape[1]
                len_cf = len(chosen_features)
                score_cf = 1 - (len_cf / total_feat)
                weight_cf = 1 - weight_score
                final_score = (weight_score * score) + (weight_cf * score_cf)
                self.feature_score_hash[feature_hash] = final_score

            if score < self.best_score:
                self.best_score = score
                self.best_dim = individual
                self.best_score_dimension = individual
            if particle_swarm_flag:
                if score < self.current_best_scores[i]:
                    self.current_best_scores[i] = score
                    self.current_best_individual_score_dimensions[i] = individual
            if dragon_fly_flag:
                if score > self.worst_score:
                    self.worst_score = score
                    self.worst_dim = individual
            scores.append(score)
        return scores

    def iteration_objective_score_monitor(self, i):
        if self.minimize:
            self.best_results_per_iteration[i] = {'best_score': self.best_score,
                                                  'objective_score': np.array(self.fitness_scores).min(),
                                                  'selected_features': list(self.feature_list[
                                                      np.where(self.individuals[np.array(self.fitness_scores).argmin()])[0]])}
        else:
            self.best_results_per_iteration[i] = {'best_score': -self.best_score,
                                                  'objective_score': -np.array(self.fitness_scores).min(),
                                                  'selected_features': list(self.feature_list[
                                                      np.where(self.individuals[np.array(self.fitness_scores).argmin()])[0]])}

    def initialize_population(self, x):
        self.individuals = np.random.randint(
            0, 2, size=(self.population_size, x.shape[1]))

    def _check_params(self, model, x_train, y_train, x_valid, y_valid):
        if (self.n_iteration <= 0):
            raise ValueError(
                f"n_init should be > 0, got {self.n_iteration} instead.")

        if (self.population_size <= 0):
            raise ValueError(
                f"population_size should be > 0, got {self.population_size} instead.")

        if (not (callable(self.objective_function))):
            raise TypeError(f"objective_function should be a callable function that returns\
                            metric value, got {type(self.objective_function)} instead")

        if y_train is None:
            raise ValueError(
                f"requires y_train to be passed, but the target y is None.")

        if x_train is None:
            raise ValueError(
                f"requires X_train to be passed, but the target X_train is None.")

        if (type(x_train) != pd.core.frame.DataFrame):
            raise TypeError(f" X_train should be of type pandas.core.frame.DataFrame,\
                            got {type(x_train)} instead.")

        if (type(x_valid) != pd.core.frame.DataFrame):
            raise TypeError(f" X_valid should be of type pandas.core.frame.DataFrame,\
                            got {type(x_valid)} instead.")

        if x_train.shape[1] != x_valid.shape[1]:
            raise ValueError(f" X_train and X_valid should have same number of features,\
                             got { x_train.shape[1]},{x_valid.shape[1]} instead.")

        if x_valid is None:
            raise ValueError(
                f"requires X_valid to be passed, but the target X_train is None.")

        if y_valid is None:
            raise ValueError(
                f"requires X_valid to be passed, but the target y_valid is None.")

        return_val = self.objective_function(
            model, x_train, y_train, x_valid, y_valid, **self.kwargs)
        if (not (isinstance(return_val, (int, float)))):
            raise TypeError(
                f"objective_function should return int/float value , got {type(return_val)} instead.")

    def plot_history(self):
        """
        Plot objective score history
        """
        res = pd.DataFrame.from_dict(self.best_results_per_iteration).T
        res.reset_index(inplace=True)
        res.columns = ['iteration', 'best_score',
                       'objective_score', 'selected_features']
        fig = go.Figure()
        fig.add_trace(go.Scatter(x=res['iteration'], y=res['objective_score'],
                                 mode='markers', name='objective_score'))
        fig.add_trace(go.Scatter(x=res['iteration'], y=res['best_score'],
                                 mode='lines+markers',
                                 name='best_score'))
        fig.update_xaxes(title_text='Iteration')
        fig.update_yaxes(title_text='objective_score')
        fig.update_layout(
            title="Optimization History Plot")
#         fig.show()
        return fig

    def _check_individuals(self):
        if (self.individuals.sum(axis=1) == 0).sum() > 0:
            log.warning(str((self.individuals.sum(axis=1) ==
                        0).sum())+' individuals went zero')
            self.individuals[self.individuals.sum(axis=1) == 0] = np.random.randint(0, 2,
                                                                                    (self.individuals[self.individuals.sum(axis=1) == 0].shape[0],
                                                                                     self.individuals[self.individuals.sum(axis=1) == 0].shape[1]))


    def _setup_logger(self):
        logger = logging.getLogger()

        if (logger.hasHandlers()):
            logger.handlers.clear()

        # Logging info level to stdout with colors
        terminal_handler = colorlog.StreamHandler()
        color_formatter = colorlog.ColoredFormatter(
            "%(green)s [ %(asctime)s ] %(reset)s%(message)s",
            datefmt=None,
            reset=True,
            log_colors={
                'DEBUG':    'cyan',
                'INFO':     'green',
                'WARNING':  'yellow',
                'ERROR':    'red',
                'CRITICAL': 'red,bg_white',
            },
            secondary_log_colors={},
            style='%'
        )
        terminal_handler.setLevel(logging.DEBUG)
        terminal_handler.setFormatter(color_formatter)

        # Add handlers to logger
        logger.addHandler(terminal_handler)

        return logger

    
    def verbose_results(self,verbose, i):
        if verbose:
            if i==0:
                if self.my_logger==None:
                    self.my_logger = self._setup_logger()

            fitness_scores = np.array(self.fitness_scores).min() if self.minimize else -np.array(self.fitness_scores).min()
            best_score = self.best_score if self.minimize else -self.best_score

            self.my_logger.warning(f"Finished iteration #{i} with objective value {fitness_scores}. Current best value is {best_score} ")


"""

Genetic Optimization Class from Zoofs library

"""
import numpy as np
import scipy
import plotly.graph_objects as go
import scipy
import time
import warnings


class GeneticOptimization(BaseOptimizationAlgorithm):
    def __init__(self,
                 objective_function,
                 n_iteration: int = 1000,
                 timeout: int = None,
                 population_size=20,
                 selective_pressure=2,
                 elitism=2,
                 mutation_rate=0.05,
                 minimize=True,
                 logger=None,
                 **kwargs):
        """
        Parameters
        ----------
        objective_function : user made function of the signature 'func(model,X_train,y_train,X_test,y_test)'
            The function must return a value, that needs to be minimized/maximized.
        n_iteration : int, default=1000
            Number of time the Optimization algorithm will run
        timeout: int = None
            Stop operation after the given number of second(s).
            If this argument is set to None, the operation is executed without time limitation and n_iteration is followed
        population_size : int, default=50
            Total size of the population
        selective_pressure : int, default=2
            measure of reproductive opportunities for each organism in the population
        elitism : int, default=2
            number of top individuals to be considered as elites
        mutation_rate :  float, default=0.05
            rate of mutation in the population's gene
        minimize : bool, default=True
            Defines if the objective value is to be maximized or minimized
        logger: Logger or None, optional (default=None)
            - accepts `logging.Logger` instance.
            
        **kwargs
            Any extra keyword argument for objective_function
        Attributes
        ----------
        best_feature_list : ndarray of shape (n_features)
            list of features with the best result of the entire run
        """
        super().__init__(objective_function, n_iteration, timeout, population_size, minimize, logger, **kwargs)
        self.n_generations = n_iteration
        self.selective_pressure = selective_pressure
        self.elitism = elitism
        self.mutation_rate = mutation_rate

    def _evaluate_fitness(self, model, x_train, y_train, x_valid, y_valid):
        scores = []
        for individual in self.individuals:
            chosen_features = [index for index in range(
                x_train.shape[1]) if individual[index] == 1]
            x_train_copy = x_train.iloc[:, chosen_features]
            x_valid_copy = x_valid.iloc[:, chosen_features]
            feature_hash = '_*_'.join(
                sorted(self.feature_list[chosen_features]))
            if feature_hash in self.feature_score_hash.keys():
                score = self.feature_score_hash[feature_hash]
            else:
                score = self.objective_function(
                    model, x_train_copy, y_train, x_valid_copy, y_valid, **self.kwargs)
                if self.minimize:
                    score = -score
                self.feature_score_hash[feature_hash] = score
## Adding feature weight 
            total_feat = X_train[selected_features_statistical].shape[1]
            len_cf = len(chosen_features)
            score_cf = 1 - (len_cf / total_feat)
            weight_score = weight_score_global
            weight_cf = 1 - weight_score
            final_score = (weight_score * score) + (weight_cf * score_cf)
            scores.append(final_score)

        self.fitness_scores = scores
        current_best_score = np.max(self.fitness_scores)
        if current_best_score > self.best_score:
            self.best_score = current_best_score
            self.best_feature_set = self.individuals[np.argmax(
                self.fitness_scores), :]

        ranks = scipy.stats.rankdata(scores, method='average')
        self.fitness_ranks = self.selective_pressure * ranks

    def _select_individuals(self, model, x_train, y_train, x_valid, y_valid):
        self._evaluate_fitness(model, x_train, y_train, x_valid, y_valid)

        sorted_individuals_fitness = sorted(
            zip(self.individuals, self.fitness_ranks), key=lambda x: x[1], reverse=True)
        elite_individuals = np.array(
            [individual for individual, fitness in sorted_individuals_fitness[:self.elitism]])

        non_elite_individuals = np.array(
            [individual[0] for individual in sorted_individuals_fitness[self.elitism:]])

        non_elite_individuals_fitness = [
            individual[1] for individual in sorted_individuals_fitness[self.elitism:]]
        selection_probability = non_elite_individuals_fitness / \
            np.sum(non_elite_individuals_fitness)

        selected_indices = np.random.choice(range(
            len(non_elite_individuals)), self.population_size//2, p=selection_probability)
        selected_individuals = non_elite_individuals[selected_indices, :]
        self.fit_individuals = np.vstack(
            (elite_individuals, selected_individuals))

    # Make me a mutant!
    def _mutate(self, array):
        mutated_array = np.copy(array)
        for idx, gene in enumerate(array):
            if np.random.random() < self.mutation_rate:
                array[idx] = 1 if gene == 0 else 0

        return mutated_array

    def _produce_next_generation(self):
        new_population = np.empty(
            shape=(self.population_size, self.individuals.shape[1]), dtype=np.int32)
        for i in range(0, self.population_size, 2):
            parents = self.fit_individuals[np.random.choice(
                self.fit_individuals.shape[0], 2, replace=False), :]
            crossover_index = np.random.randint(0, len(self.individuals[0]))
            new_population[i] = np.hstack(
                (parents[0][:crossover_index], parents[1][crossover_index:]))
            new_population[i+1] = np.hstack(
                (parents[1][:crossover_index], parents[0][crossover_index:]))

            new_population[i] = self._mutate(new_population[i])
            new_population[i+1] = self._mutate(new_population[i+1])
        self.individuals = new_population

    def _verbose_results(self, verbose, i):
        if verbose:
            if i == 0:
                print(
                    "\t\t Best value of metric across iteration \t Best value of metric across population  ")
            if self.minimize:
                print(
                    f"Iteration {i} \t {-np.array(self.fitness_scores).max()} \t\t\t\t\t {-self.best_score} ")
            else:
                print(
                    f"Iteration {i} \t {np.array(self.fitness_scores).max()} \t\t\t\t\t {self.best_score} ")

    def _iteration_objective_score_monitor(self, i):
        if self.minimize:
            self.best_results_per_iteration[i] = {'best_score': -self.best_score,
                                                  'objective_score': -np.array(self.fitness_scores).max(),
                                                  'selected_features': list(self.feature_list[
                                                      np.where(self.individuals[np.array(self.fitness_scores).argmin()])[0]])}
        else:
            self.best_results_per_iteration[i] = {'best_score': self.best_score,
                                                  'objective_score': np.array(self.fitness_scores).max(),
                                                  'selected_features': list(self.feature_list[
                                                      np.where(self.individuals[np.array(self.fitness_scores).argmin()])[0]])}

    def fit(self, model, X_train, y_train, X_valid, y_valid, verbose=True):
        """
        Parameters
        ----------      
        model : machine learning model's object
           machine learning model's object
        X_train : pandas.core.frame.DataFrame of shape (n_samples, n_features)
           Training input samples to be used for machine learning model
        y_train : pandas.core.frame.DataFrame or pandas.core.series.Series of shape (n_samples)
           The target values (class labels in classification, real numbers in regression).
        X_valid : pandas.core.frame.DataFrame of shape (n_samples, n_features)
           Validation input samples
        y_valid : pandas.core.frame.DataFrame or pandas.core.series.Series of shape (n_samples)
            The target values (class labels in classification, real numbers in regression).                
        verbose : bool,default=True
             Print results for iterations
        """
        self._check_params(model, X_train, y_train, X_valid, y_valid)

        self.feature_score_hash = {}
        self.feature_list = np.array(list(X_train.columns))
        self.best_results_per_iteration = {}
        self.best_score = np.inf
        self.best_dim = np.ones(X_train.shape[1])

        self.initialize_population(X_train)
        self.best_score = -1 * float(np.inf)
        self.best_scores = []

        if (self.timeout is not None):
            timeout_upper_limit = time.time() + self.timeout
        else:
            timeout_upper_limit = time.time()
        for i in range(self.n_generations):

            if (self.timeout is not None) & (time.time() > timeout_upper_limit):
                warnings.warn("Timeout occured")
                break
            self._select_individuals(model, X_train, y_train, X_valid, y_valid)
            self._produce_next_generation()
            self.best_scores.append(self.best_score)

            self._iteration_objective_score_monitor(i)
            self._verbose_results(verbose, i)
            self.best_feature_list = list(
                self.feature_list[np.where(self.best_dim)[0]])
        return self.best_feature_list


"""

Input : X_train(selected_features_statistical)

Output:

linear => selected feature + best_score 20 run
rbf => selected feature + best_score 20 run
poly => selected feature + best_score 20 run


"""

'\n\nInput : X_train(selected_features_statistical)\n\nOutput:\n\nlinear => selected feature + best_score 20 run\npoly => selected feature + best_score 20 run\nrbf => selected feature + best_score 20 run\n\n'


from sklearn.svm import SVR
from sklearn.pipeline import make_pipeline
from sklearn.metrics import r2_score
from sklearn.model_selection import cross_val_score


### Preparing X_train for GA Features Selection
X_train = X_train_scaled[selected_features_statistical]


### Dummy x_valid and y_valid (not used in objective function)
X_valid = train.iloc[:,:-1]
X_valid = X_valid[selected_features_statistical]
y_valid = train.iloc[:, [-1]]


# define your own objective function, make sure the function receives four parameters,
#  fit your model and return the objective value ! 
def objective_function_topass(model, X_train, y_train, X_valid, y_valid):      
    # Using CV to calculate scores
    score = cross_val_score(model, X_train, y_train, scoring='r2', cv=5, n_jobs=-1)
    score = score.mean()
    return score

def features_select_GA(model, X_train, y_train, X_valid, y_valid):
    # create object of algorithm
    algo_object=GeneticOptimization(objective_function_topass,n_iteration=50,
                                population_size=20,selective_pressure=2,elitism=2,
                                mutation_rate=0.05,minimize=False)


    # fit the algorithm
    algo_object.fit(model, X_train, y_train.values.ravel(), X_valid, y_valid.values.ravel(), verbose=True)

    #plot your results
    # algo_object.plot_history()

    # extract the best  feature set
    # algo_object.best_feature_list 
    return algo_object


def multiple_run_fs(n_runs, model, X_train, y_train, X_valid, y_valid):
    all_solutions = {}
    best_solution = {}
    best_score  = 0
    
    
    for i in range(n_runs):
        print("\n\n ----------------------------------------------------------------------------------------")
        print(f"Run Number - {i+1}")
        current_solution = {}
        
        solution_obj = features_select_GA(model, X_train, y_train, X_valid, y_valid)
        last_key = max(solution_obj.best_results_per_iteration.keys())
        
        # solution per run time
        solution_score = solution_obj.best_scores[last_key]
        len_solution = len(solution_obj.best_results_per_iteration[last_key]['selected_features'])
        list_selected_features = solution_obj.best_results_per_iteration[last_key]['selected_features']
        plot = solution_obj.plot_history()
        
        current_solution['score'] = solution_score
        current_solution['num_features'] = len_solution
        current_solution['selected_features'] = list_selected_features
        current_solution['plot'] = plot
        
        # Finding best score over runtimes
        if (solution_score > best_score):
            best_score = solution_score #update best score over runtimes 
            best_solution['run_id'] = i+1
            best_solution['best_score'] = solution_score
            best_solution['num_features'] = len_solution
            best_solution['selected_features'] = list_selected_features
            best_solution['plot'] = plot
            
        # save all solution with run id as the key
        all_solutions[i+1] = current_solution
    # END of LOOP
    # append best_solution into all_solution dict
    all_solutions['best_solution'] = best_solution
    
    # return dictionaries of all salution
    return all_solutions


def multiple_run_fs_dataframe(n_runs, model, X_train, y_train, X_valid, y_valid):

    run_id = []
    num_features = []
    objective_scores = []
    best_scores = []
    selected_features = []
    plots = []
    
    
    for i in range(n_runs):
        print("\n\n ----------------------------------------------------------------------------------------")
        print(f"Run Id - {i+1}")
        best_objective_score = 0
        
        solution_obj = features_select_GA(model, X_train, y_train, X_valid, y_valid)
        
        # Best key per GA iteration
        # last_key = max(solution_obj.best_results_per_iteration.keys())
        for j in range(len(solution_obj.best_results_per_iteration)):
            if solution_obj.best_results_per_iteration[j]['objective_score'] > best_objective_score:
                best_objective_score = solution_obj.best_results_per_iteration[j]['objective_score']
                best_key = j
        
        # solution per run time
        solution_objective_score = solution_obj.best_results_per_iteration[best_key]['objective_score']
        solution_best_score = solution_obj.best_results_per_iteration[best_key]['best_score']
        len_solution = len(solution_obj.best_results_per_iteration[best_key]['selected_features'])
        list_selected_features = solution_obj.best_results_per_iteration[best_key]['selected_features']
        plot = solution_obj.plot_history()
        
        # append solution into a list
        run_id.append(i+1)
        num_features.append(len_solution)
        objective_scores.append(solution_objective_score)
        best_scores.append(solution_best_score)
        selected_features.append(list_selected_features)
        plots.append(plot)
        
    # END of LOOP
    
    # Create dataframe of the solutions
    dict_solution = {'run_id': run_id, 'num_features': num_features, 'objective_scores' : objective_scores,
                    'best_scores' : best_scores, 'selected_features' : selected_features, 'plot' : plots}
    df_solution = pd.DataFrame(data=dict_solution)
    
    # return dictionaries of all salution
    return df_solution


### TEST NEW FUNCTION

# Define machine learning model
svr_linear_model = SVR(kernel='rbf')
# Multiple run GA with those machine learning model
solutions_linear_df = multiple_run_fs_dataframe(3, svr_linear_model, X_train, y_train, X_valid, y_valid)
solutions_linear_df


 ----------------------------------------------------------------------------------------
Run Id - 1
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6443083097942265 					 0.6443083097942265 
Iteration 1 	 0.6443083097942265 					 0.6443083097942265 
Iteration 2 	 0.6453829061852276 					 0.6453829061852276 
Iteration 3 	 0.6425039955362051 					 0.6453829061852276 
Iteration 4 	 0.6418910589223105 					 0.6453829061852276 
Iteration 5 	 0.6418910589223105 					 0.6453829061852276 
Iteration 6 	 0.6418910589223105 					 0.6453829061852276 
Iteration 7 	 0.6431817306946149 					 0.6453829061852276 
Iteration 8 	 0.6434492609203828 					 0.6453829061852276 
Iteration 9 	 0.642575901979776 					 0.6453829061852276 
Iteration 10 	 0.642575901979776 					 0.6453829061852276 
Iteration 11 	 0.642575901979776 					 0.6453829061852276 
Iteration 12 	 0.642575901979776 					 0.6453829061852276 
Iteration 13 	 0.642575901979776 					 0.6453829061852276 
Iteration 14 	 0.642575901979776 					 0.6453829061852276 
Iteration 15 	 0.642575901979776 					 0.6453829061852276 
Iteration 16 	 0.642575901979776 					 0.6453829061852276 
Iteration 17 	 0.642575901979776 					 0.6453829061852276 
Iteration 18 	 0.642575901979776 					 0.6453829061852276 
Iteration 19 	 0.642575901979776 					 0.6453829061852276 
Iteration 20 	 0.642575901979776 					 0.6453829061852276 
Iteration 21 	 0.642575901979776 					 0.6453829061852276 
Iteration 22 	 0.642575901979776 					 0.6453829061852276 
Iteration 23 	 0.642575901979776 					 0.6453829061852276 
Iteration 24 	 0.642575901979776 					 0.6453829061852276 
Iteration 25 	 0.642575901979776 					 0.6453829061852276 
Iteration 26 	 0.642575901979776 					 0.6453829061852276 
Iteration 27 	 0.642575901979776 					 0.6453829061852276 
Iteration 28 	 0.642575901979776 					 0.6453829061852276 
Iteration 29 	 0.642575901979776 					 0.6453829061852276 
Iteration 30 	 0.642575901979776 					 0.6453829061852276 
Iteration 31 	 0.642575901979776 					 0.6453829061852276 
Iteration 32 	 0.642575901979776 					 0.6453829061852276 
Iteration 33 	 0.642575901979776 					 0.6453829061852276 
Iteration 34 	 0.642575901979776 					 0.6453829061852276 
Iteration 35 	 0.642575901979776 					 0.6453829061852276 
Iteration 36 	 0.642575901979776 					 0.6453829061852276 
Iteration 37 	 0.642575901979776 					 0.6453829061852276 
Iteration 38 	 0.642575901979776 					 0.6453829061852276 
Iteration 39 	 0.642575901979776 					 0.6453829061852276 
Iteration 40 	 0.642575901979776 					 0.6453829061852276 
Iteration 41 	 0.642575901979776 					 0.6453829061852276 
Iteration 42 	 0.642575901979776 					 0.6453829061852276 
Iteration 43 	 0.642575901979776 					 0.6453829061852276 
Iteration 44 	 0.642575901979776 					 0.6453829061852276 
Iteration 45 	 0.642575901979776 					 0.6453829061852276 
Iteration 46 	 0.642575901979776 					 0.6453829061852276 
Iteration 47 	 0.642575901979776 					 0.6453829061852276 
Iteration 48 	 0.642575901979776 					 0.6453829061852276 
Iteration 49 	 0.642575901979776 					 0.6453829061852276 


 ----------------------------------------------------------------------------------------
Run Id - 2
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6399307448638114 					 0.6399307448638114 
Iteration 1 	 0.6452327350281386 					 0.6452327350281386 
Iteration 2 	 0.6452327350281386 					 0.6452327350281386 
Iteration 3 	 0.651499899740315 					 0.651499899740315 
Iteration 4 	 0.6505618667185235 					 0.651499899740315 
Iteration 5 	 0.6505618667185235 					 0.651499899740315 
Iteration 6 	 0.6538489154696985 					 0.6538489154696985 
Iteration 7 	 0.6535401741846716 					 0.6538489154696985 
Iteration 8 	 0.6546790266230885 					 0.6546790266230885 
Iteration 9 	 0.6566201727737322 					 0.6566201727737322 
Iteration 10 	 0.6553528436200945 					 0.6566201727737322 
Iteration 11 	 0.6564634589626933 					 0.6566201727737322 
Iteration 12 	 0.6561167281643371 					 0.6566201727737322 
Iteration 13 	 0.656438694904687 					 0.6566201727737322 
Iteration 14 	 0.6598754185561186 					 0.6598754185561186 
Iteration 15 	 0.6586380805515534 					 0.6598754185561186 
Iteration 16 	 0.656438694904687 					 0.6598754185561186 
Iteration 17 	 0.65648706156211 					 0.6598754185561186 
Iteration 18 	 0.6570306761630275 					 0.6598754185561186 
Iteration 19 	 0.6570306761630275 					 0.6598754185561186 
Iteration 20 	 0.6570306761630275 					 0.6598754185561186 
Iteration 21 	 0.6570306761630275 					 0.6598754185561186 
Iteration 22 	 0.6570306761630275 					 0.6598754185561186 
Iteration 23 	 0.6570306761630275 					 0.6598754185561186 
Iteration 24 	 0.6570306761630275 					 0.6598754185561186 
Iteration 25 	 0.6570306761630275 					 0.6598754185561186 
Iteration 26 	 0.6570306761630275 					 0.6598754185561186 
Iteration 27 	 0.6570306761630275 					 0.6598754185561186 
Iteration 28 	 0.6570306761630275 					 0.6598754185561186 
Iteration 29 	 0.6570306761630275 					 0.6598754185561186 
Iteration 30 	 0.6570306761630275 					 0.6598754185561186 
Iteration 31 	 0.6570306761630275 					 0.6598754185561186 
Iteration 32 	 0.6570306761630275 					 0.6598754185561186 
Iteration 33 	 0.6570306761630275 					 0.6598754185561186 
Iteration 34 	 0.6570306761630275 					 0.6598754185561186 
Iteration 35 	 0.6570306761630275 					 0.6598754185561186 
Iteration 36 	 0.6570306761630275 					 0.6598754185561186 
Iteration 37 	 0.6570306761630275 					 0.6598754185561186 
Iteration 38 	 0.6570306761630275 					 0.6598754185561186 
Iteration 39 	 0.6570306761630275 					 0.6598754185561186 
Iteration 40 	 0.6570306761630275 					 0.6598754185561186 
Iteration 41 	 0.6570306761630275 					 0.6598754185561186 
Iteration 42 	 0.6570306761630275 					 0.6598754185561186 
Iteration 43 	 0.6570306761630275 					 0.6598754185561186 
Iteration 44 	 0.6570306761630275 					 0.6598754185561186 
Iteration 45 	 0.6570306761630275 					 0.6598754185561186 
Iteration 46 	 0.6570306761630275 					 0.6598754185561186 
Iteration 47 	 0.6570306761630275 					 0.6598754185561186 
Iteration 48 	 0.6570306761630275 					 0.6598754185561186 
Iteration 49 	 0.6570306761630275 					 0.6598754185561186 


 ----------------------------------------------------------------------------------------
Run Id - 3
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6405681943959847 					 0.6405681943959847 
Iteration 1 	 0.6461167722993006 					 0.6461167722993006 
Iteration 2 	 0.6502792473450579 					 0.6502792473450579 
Iteration 3 	 0.6554248192651473 					 0.6554248192651473 
Iteration 4 	 0.6541100824260601 					 0.6554248192651473 
Iteration 5 	 0.6543159363277852 					 0.6554248192651473 
Iteration 6 	 0.6543159363277852 					 0.6554248192651473 
Iteration 7 	 0.6543159363277852 					 0.6554248192651473 
Iteration 8 	 0.6543159363277852 					 0.6554248192651473 
Iteration 9 	 0.6543159363277852 					 0.6554248192651473 
Iteration 10 	 0.6543159363277852 					 0.6554248192651473 
Iteration 11 	 0.6543159363277852 					 0.6554248192651473 
Iteration 12 	 0.6548277486634176 					 0.6554248192651473 
Iteration 13 	 0.6543159363277852 					 0.6554248192651473 
Iteration 14 	 0.6543159363277852 					 0.6554248192651473 
Iteration 15 	 0.6543159363277852 					 0.6554248192651473 
Iteration 16 	 0.6543159363277852 					 0.6554248192651473 
Iteration 17 	 0.6543159363277852 					 0.6554248192651473 
Iteration 18 	 0.6543159363277852 					 0.6554248192651473 
Iteration 19 	 0.6543159363277852 					 0.6554248192651473 
Iteration 20 	 0.6543159363277852 					 0.6554248192651473 
Iteration 21 	 0.6543159363277852 					 0.6554248192651473 
Iteration 22 	 0.6543159363277852 					 0.6554248192651473 
Iteration 23 	 0.6543159363277852 					 0.6554248192651473 
Iteration 24 	 0.6543159363277852 					 0.6554248192651473 
Iteration 25 	 0.6543159363277852 					 0.6554248192651473 
Iteration 26 	 0.6543159363277852 					 0.6554248192651473 
Iteration 27 	 0.6543159363277852 					 0.6554248192651473 
Iteration 28 	 0.6543159363277852 					 0.6554248192651473 
Iteration 29 	 0.6543159363277852 					 0.6554248192651473 
Iteration 30 	 0.6543159363277852 					 0.6554248192651473 
Iteration 31 	 0.6543159363277852 					 0.6554248192651473 
Iteration 32 	 0.6543159363277852 					 0.6554248192651473 
Iteration 33 	 0.6543159363277852 					 0.6554248192651473 
Iteration 34 	 0.6543159363277852 					 0.6554248192651473 
Iteration 35 	 0.6543159363277852 					 0.6554248192651473 
Iteration 36 	 0.6543159363277852 					 0.6554248192651473 
Iteration 37 	 0.6543159363277852 					 0.6554248192651473 
Iteration 38 	 0.6543159363277852 					 0.6554248192651473 
Iteration 39 	 0.6543159363277852 					 0.6554248192651473 
Iteration 40 	 0.6543159363277852 					 0.6554248192651473 
Iteration 41 	 0.6543159363277852 					 0.6554248192651473 
Iteration 42 	 0.6543159363277852 					 0.6554248192651473 
Iteration 43 	 0.6543159363277852 					 0.6554248192651473 
Iteration 44 	 0.6543159363277852 					 0.6554248192651473 
Iteration 45 	 0.6543159363277852 					 0.6554248192651473 
Iteration 46 	 0.6543159363277852 					 0.6554248192651473 
Iteration 47 	 0.6543159363277852 					 0.6554248192651473 
Iteration 48 	 0.6543159363277852 					 0.6554248192651473 
Iteration 49 	 0.6543159363277852 					 0.6554248192651473


# Define machine learning model
svr_linear_model = SVR(kernel='rbf')
# Multiple run GA with those machine learning model
solutions_linear_df = multiple_run_fs_dataframe(3, svr_linear_model, X_train, y_train, X_valid, y_valid)
solutions_linear_df


# Define machine learning model
svr_linear_model = SVR(kernel='rbf')
# Multiple run GA with those machine learning model
solutions_linear_df = multiple_run_fs_dataframe(3, svr_linear_model, X_train, y_train, X_valid, y_valid)
solutions_linear_df


# # Define machine learning model
# svr_linear_model = SVR(kernel='linear')
# # Multiple run GA with those machine learning model
# solutions_linear = multiple_run_fs(20, svr_linear_model, X_train, y_train, X_valid, y_valid)


 ----------------------------------------------------------------------------------------
Run Number - 1
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.46443922562090123 					 0.46443922562090123 
Iteration 1 	 0.4154698687221213 					 0.46443922562090123 
Iteration 2 	 0.4380734751305624 					 0.46443922562090123 
Iteration 3 	 0.473572230807073 					 0.473572230807073 
Iteration 4 	 0.5045553450881772 					 0.5045553450881772 
Iteration 5 	 0.5274916556556529 					 0.5274916556556529 
Iteration 6 	 0.5270386140882354 					 0.5274916556556529 
Iteration 7 	 0.5308105032387859 					 0.5308105032387859 
Iteration 8 	 0.5308105032387859 					 0.5308105032387859 
Iteration 9 	 0.5246150553187487 					 0.5308105032387859 
Iteration 10 	 0.5041079580466618 					 0.5308105032387859 
Iteration 11 	 0.5041079580466618 					 0.5308105032387859 
Iteration 12 	 0.5041079580466618 					 0.5308105032387859 
Iteration 13 	 0.5041079580466618 					 0.5308105032387859 
Iteration 14 	 0.5041079580466618 					 0.5308105032387859 
Iteration 15 	 0.5041079580466618 					 0.5308105032387859 
Iteration 16 	 0.5041079580466618 					 0.5308105032387859 
Iteration 17 	 0.5041079580466618 					 0.5308105032387859 
Iteration 18 	 0.5041079580466618 					 0.5308105032387859 
Iteration 19 	 0.5041079580466618 					 0.5308105032387859 
Iteration 20 	 0.5041079580466618 					 0.5308105032387859 
Iteration 21 	 0.5041079580466618 					 0.5308105032387859 
Iteration 22 	 0.5041079580466618 					 0.5308105032387859 
Iteration 23 	 0.5041079580466618 					 0.5308105032387859 
Iteration 24 	 0.5041079580466618 					 0.5308105032387859 
Iteration 25 	 0.5041079580466618 					 0.5308105032387859 
Iteration 26 	 0.5041079580466618 					 0.5308105032387859 
Iteration 27 	 0.5041079580466618 					 0.5308105032387859 
Iteration 28 	 0.5041079580466618 					 0.5308105032387859 
Iteration 29 	 0.5041079580466618 					 0.5308105032387859 
Iteration 30 	 0.5041079580466618 					 0.5308105032387859 
Iteration 31 	 0.5041079580466618 					 0.5308105032387859 
Iteration 32 	 0.5041079580466618 					 0.5308105032387859 
Iteration 33 	 0.5041079580466618 					 0.5308105032387859 
Iteration 34 	 0.5041079580466618 					 0.5308105032387859 
Iteration 35 	 0.5041079580466618 					 0.5308105032387859 
Iteration 36 	 0.5041079580466618 					 0.5308105032387859 
Iteration 37 	 0.5041079580466618 					 0.5308105032387859 
Iteration 38 	 0.5041079580466618 					 0.5308105032387859 
Iteration 39 	 0.5041079580466618 					 0.5308105032387859 
Iteration 40 	 0.5041079580466618 					 0.5308105032387859 
Iteration 41 	 0.5041079580466618 					 0.5308105032387859 
Iteration 42 	 0.5041079580466618 					 0.5308105032387859 
Iteration 43 	 0.5041079580466618 					 0.5308105032387859 
Iteration 44 	 0.5041079580466618 					 0.5308105032387859 
Iteration 45 	 0.5041079580466618 					 0.5308105032387859 
Iteration 46 	 0.5041079580466618 					 0.5308105032387859 
Iteration 47 	 0.5041079580466618 					 0.5308105032387859 
Iteration 48 	 0.5041079580466618 					 0.5308105032387859 
Iteration 49 	 0.5041079580466618 					 0.5308105032387859 


 ----------------------------------------------------------------------------------------
Run Number - 2
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.43569054651654665 					 0.43569054651654665 
Iteration 1 	 0.35674236246047675 					 0.43569054651654665 
Iteration 2 	 0.40554285176442006 					 0.43569054651654665 
Iteration 3 	 0.41931800347822196 					 0.43569054651654665 
Iteration 4 	 0.5072843907995461 					 0.5072843907995461 
Iteration 5 	 0.5125785663133281 					 0.5125785663133281 
Iteration 6 	 0.5125785663133281 					 0.5125785663133281 
Iteration 7 	 0.5136077666526457 					 0.5136077666526457 
Iteration 8 	 0.5125785663133281 					 0.5136077666526457 
Iteration 9 	 0.522977707768359 					 0.522977707768359 
Iteration 10 	 0.531318523218786 					 0.531318523218786 
Iteration 11 	 0.5433334722556828 					 0.5433334722556828 
Iteration 12 	 0.5421458428774132 					 0.5433334722556828 
Iteration 13 	 0.5433334722556828 					 0.5433334722556828 
Iteration 14 	 0.5433334722556828 					 0.5433334722556828 
Iteration 15 	 0.5433334722556828 					 0.5433334722556828 
Iteration 16 	 0.5433334722556828 					 0.5433334722556828 
Iteration 17 	 0.5433334722556828 					 0.5433334722556828 
Iteration 18 	 0.5433334722556828 					 0.5433334722556828 
Iteration 19 	 0.5433334722556828 					 0.5433334722556828 
Iteration 20 	 0.5433334722556828 					 0.5433334722556828 
Iteration 21 	 0.5433334722556828 					 0.5433334722556828 
Iteration 22 	 0.5433334722556828 					 0.5433334722556828 
Iteration 23 	 0.5433334722556828 					 0.5433334722556828 
Iteration 24 	 0.5433334722556828 					 0.5433334722556828 
Iteration 25 	 0.5433334722556828 					 0.5433334722556828 
Iteration 26 	 0.5433334722556828 					 0.5433334722556828 
Iteration 27 	 0.5433334722556828 					 0.5433334722556828 
Iteration 28 	 0.5433334722556828 					 0.5433334722556828 
Iteration 29 	 0.5433334722556828 					 0.5433334722556828 
Iteration 30 	 0.5433334722556828 					 0.5433334722556828 
Iteration 31 	 0.5433334722556828 					 0.5433334722556828 
Iteration 32 	 0.5433334722556828 					 0.5433334722556828 
Iteration 33 	 0.5433334722556828 					 0.5433334722556828 
Iteration 34 	 0.5433334722556828 					 0.5433334722556828 
Iteration 35 	 0.5433334722556828 					 0.5433334722556828 
Iteration 36 	 0.5433334722556828 					 0.5433334722556828 
Iteration 37 	 0.5433334722556828 					 0.5433334722556828 
Iteration 38 	 0.5433334722556828 					 0.5433334722556828 
Iteration 39 	 0.5433334722556828 					 0.5433334722556828 
Iteration 40 	 0.5433334722556828 					 0.5433334722556828 
Iteration 41 	 0.5433334722556828 					 0.5433334722556828 
Iteration 42 	 0.5433334722556828 					 0.5433334722556828 
Iteration 43 	 0.5433334722556828 					 0.5433334722556828 
Iteration 44 	 0.5433334722556828 					 0.5433334722556828 
Iteration 45 	 0.5433334722556828 					 0.5433334722556828 
Iteration 46 	 0.5433334722556828 					 0.5433334722556828 
Iteration 47 	 0.5433334722556828 					 0.5433334722556828 
Iteration 48 	 0.5433334722556828 					 0.5433334722556828 
Iteration 49 	 0.5433334722556828 					 0.5433334722556828 


 ----------------------------------------------------------------------------------------
Run Number - 3
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.49823428857528296 					 0.49823428857528296 
Iteration 1 	 0.49738272159738833 					 0.49823428857528296 
Iteration 2 	 0.4531624843885085 					 0.49823428857528296 
Iteration 3 	 0.49738272159738833 					 0.49823428857528296 
Iteration 4 	 0.5014123062390823 					 0.5014123062390823 
Iteration 5 	 0.4988802421427642 					 0.5014123062390823 
Iteration 6 	 0.4981226906807027 					 0.5014123062390823 
Iteration 7 	 0.4981226906807027 					 0.5014123062390823 
Iteration 8 	 0.509316322076002 					 0.509316322076002 
Iteration 9 	 0.509316322076002 					 0.509316322076002 
Iteration 10 	 0.49957744912697816 					 0.509316322076002 
Iteration 11 	 0.49914449592143056 					 0.509316322076002 
Iteration 12 	 0.49914449592143056 					 0.509316322076002 
Iteration 13 	 0.5019153497267728 					 0.509316322076002 
Iteration 14 	 0.49914449592143056 					 0.509316322076002 
Iteration 15 	 0.5013973199123244 					 0.509316322076002 
Iteration 16 	 0.5067816884190295 					 0.509316322076002 
Iteration 17 	 0.5093738972546042 					 0.5093738972546042 
Iteration 18 	 0.5093738972546042 					 0.5093738972546042 
Iteration 19 	 0.5093738972546042 					 0.5093738972546042 
Iteration 20 	 0.5093738972546042 					 0.5093738972546042 
Iteration 21 	 0.5093738972546042 					 0.5093738972546042 
Iteration 22 	 0.5097500767725848 					 0.5097500767725848 
Iteration 23 	 0.5097500767725848 					 0.5097500767725848 
Iteration 24 	 0.5097500767725848 					 0.5097500767725848 
Iteration 25 	 0.5097500767725848 					 0.5097500767725848 
Iteration 26 	 0.5097500767725848 					 0.5097500767725848 
Iteration 27 	 0.5097500767725848 					 0.5097500767725848 
Iteration 28 	 0.5097500767725848 					 0.5097500767725848 
Iteration 29 	 0.5097500767725848 					 0.5097500767725848 
Iteration 30 	 0.5097500767725848 					 0.5097500767725848 
Iteration 31 	 0.5097500767725848 					 0.5097500767725848 
Iteration 32 	 0.5097500767725848 					 0.5097500767725848 
Iteration 33 	 0.5097500767725848 					 0.5097500767725848 
Iteration 34 	 0.5097500767725848 					 0.5097500767725848 
Iteration 35 	 0.5097500767725848 					 0.5097500767725848 
Iteration 36 	 0.5097500767725848 					 0.5097500767725848 
Iteration 37 	 0.5097500767725848 					 0.5097500767725848 
Iteration 38 	 0.5097500767725848 					 0.5097500767725848 
Iteration 39 	 0.5097500767725848 					 0.5097500767725848 
Iteration 40 	 0.5097500767725848 					 0.5097500767725848 
Iteration 41 	 0.5097500767725848 					 0.5097500767725848 
Iteration 42 	 0.5097500767725848 					 0.5097500767725848 
Iteration 43 	 0.5097500767725848 					 0.5097500767725848 
Iteration 44 	 0.5097500767725848 					 0.5097500767725848 
Iteration 45 	 0.5097500767725848 					 0.5097500767725848 
Iteration 46 	 0.5097500767725848 					 0.5097500767725848 
Iteration 47 	 0.5097500767725848 					 0.5097500767725848 
Iteration 48 	 0.5097500767725848 					 0.5097500767725848 
Iteration 49 	 0.5097500767725848 					 0.5097500767725848 


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Run Number - 4
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.323588392310782 					 0.323588392310782 
Iteration 1 	 0.2847741603671029 					 0.323588392310782 
Iteration 2 	 0.36037113617864525 					 0.36037113617864525 
Iteration 3 	 0.3571164236584326 					 0.36037113617864525 
Iteration 4 	 0.38636379899531603 					 0.38636379899531603 
Iteration 5 	 0.3831278253199394 					 0.38636379899531603 
Iteration 6 	 0.38679112195364473 					 0.38679112195364473 
Iteration 7 	 0.38903154149438973 					 0.38903154149438973 
Iteration 8 	 0.40062546701044693 					 0.40062546701044693 
Iteration 9 	 0.40062546701044693 					 0.40062546701044693 
Iteration 10 	 0.40062546701044693 					 0.40062546701044693 
Iteration 11 	 0.4031529214887137 					 0.4031529214887137 
Iteration 12 	 0.4031529214887137 					 0.4031529214887137 
Iteration 13 	 0.4031529214887137 					 0.4031529214887137 
Iteration 14 	 0.4031529214887137 					 0.4031529214887137 
Iteration 15 	 0.4031529214887137 					 0.4031529214887137 
Iteration 16 	 0.4031529214887137 					 0.4031529214887137 
Iteration 17 	 0.4031529214887137 					 0.4031529214887137 
Iteration 18 	 0.4031529214887137 					 0.4031529214887137 
Iteration 19 	 0.4031529214887137 					 0.4031529214887137 
Iteration 20 	 0.4031529214887137 					 0.4031529214887137 
Iteration 21 	 0.4031529214887137 					 0.4031529214887137 
Iteration 22 	 0.4031529214887137 					 0.4031529214887137 
Iteration 23 	 0.4031529214887137 					 0.4031529214887137 
Iteration 24 	 0.4031529214887137 					 0.4031529214887137 
Iteration 25 	 0.4031529214887137 					 0.4031529214887137 
Iteration 26 	 0.4031529214887137 					 0.4031529214887137 
Iteration 27 	 0.4031529214887137 					 0.4031529214887137 
Iteration 28 	 0.4031529214887137 					 0.4031529214887137 
Iteration 29 	 0.4031529214887137 					 0.4031529214887137 
Iteration 30 	 0.4031529214887137 					 0.4031529214887137 
Iteration 31 	 0.4031529214887137 					 0.4031529214887137 
Iteration 32 	 0.4031529214887137 					 0.4031529214887137 
Iteration 33 	 0.4031529214887137 					 0.4031529214887137 
Iteration 34 	 0.4031529214887137 					 0.4031529214887137 
Iteration 35 	 0.4031529214887137 					 0.4031529214887137 
Iteration 36 	 0.4031529214887137 					 0.4031529214887137 
Iteration 37 	 0.4031529214887137 					 0.4031529214887137 
Iteration 38 	 0.4031529214887137 					 0.4031529214887137 
Iteration 39 	 0.4031529214887137 					 0.4031529214887137 
Iteration 40 	 0.4031529214887137 					 0.4031529214887137 
Iteration 41 	 0.4031529214887137 					 0.4031529214887137 
Iteration 42 	 0.4031529214887137 					 0.4031529214887137 
Iteration 43 	 0.4031529214887137 					 0.4031529214887137 
Iteration 44 	 0.4031529214887137 					 0.4031529214887137 
Iteration 45 	 0.4031529214887137 					 0.4031529214887137 
Iteration 46 	 0.4031529214887137 					 0.4031529214887137 
Iteration 47 	 0.4031529214887137 					 0.4031529214887137 
Iteration 48 	 0.4031529214887137 					 0.4031529214887137 
Iteration 49 	 0.4031529214887137 					 0.4031529214887137 


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Run Number - 5
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4112560557497797 					 0.4112560557497797 
Iteration 1 	 0.4070599824786495 					 0.4112560557497797 
Iteration 2 	 0.4866686304914949 					 0.4866686304914949 
Iteration 3 	 0.4492892004608818 					 0.4866686304914949 
Iteration 4 	 0.4570004730554477 					 0.4866686304914949 
Iteration 5 	 0.45756618240348335 					 0.4866686304914949 
Iteration 6 	 0.5139353535070262 					 0.5139353535070262 
Iteration 7 	 0.4577722413728725 					 0.5139353535070262 
Iteration 8 	 0.490322179795775 					 0.5139353535070262 
Iteration 9 	 0.490322179795775 					 0.5139353535070262 
Iteration 10 	 0.5304530346045166 					 0.5304530346045166 
Iteration 11 	 0.5304530346045166 					 0.5304530346045166 
Iteration 12 	 0.5304530346045166 					 0.5304530346045166 
Iteration 13 	 0.534575425115115 					 0.534575425115115 
Iteration 14 	 0.5366553298261824 					 0.5366553298261824 
Iteration 15 	 0.5368630159721804 					 0.5368630159721804 
Iteration 16 	 0.5366553298261824 					 0.5368630159721804 
Iteration 17 	 0.5533319100621696 					 0.5533319100621696 
Iteration 18 	 0.5533319100621696 					 0.5533319100621696 
Iteration 19 	 0.5533319100621696 					 0.5533319100621696 
Iteration 20 	 0.5533319100621696 					 0.5533319100621696 
Iteration 21 	 0.5533319100621696 					 0.5533319100621696 
Iteration 22 	 0.5533319100621696 					 0.5533319100621696 
Iteration 23 	 0.5533319100621696 					 0.5533319100621696 
Iteration 24 	 0.5533319100621696 					 0.5533319100621696 
Iteration 25 	 0.5533319100621696 					 0.5533319100621696 
Iteration 26 	 0.5533319100621696 					 0.5533319100621696 
Iteration 27 	 0.5533319100621696 					 0.5533319100621696 
Iteration 28 	 0.5533319100621696 					 0.5533319100621696 
Iteration 29 	 0.5533319100621696 					 0.5533319100621696 
Iteration 30 	 0.5533319100621696 					 0.5533319100621696 
Iteration 31 	 0.5533319100621696 					 0.5533319100621696 
Iteration 32 	 0.5533319100621696 					 0.5533319100621696 
Iteration 33 	 0.5533319100621696 					 0.5533319100621696 
Iteration 34 	 0.5533319100621696 					 0.5533319100621696 
Iteration 35 	 0.5533319100621696 					 0.5533319100621696 
Iteration 36 	 0.5533319100621696 					 0.5533319100621696 
Iteration 37 	 0.5533319100621696 					 0.5533319100621696 
Iteration 38 	 0.5533319100621696 					 0.5533319100621696 
Iteration 39 	 0.5533319100621696 					 0.5533319100621696 
Iteration 40 	 0.5533319100621696 					 0.5533319100621696 
Iteration 41 	 0.5533319100621696 					 0.5533319100621696 
Iteration 42 	 0.5533319100621696 					 0.5533319100621696 
Iteration 43 	 0.5533319100621696 					 0.5533319100621696 
Iteration 44 	 0.5533319100621696 					 0.5533319100621696 
Iteration 45 	 0.5533319100621696 					 0.5533319100621696 
Iteration 46 	 0.5533319100621696 					 0.5533319100621696 
Iteration 47 	 0.5533319100621696 					 0.5533319100621696 
Iteration 48 	 0.5533319100621696 					 0.5533319100621696 
Iteration 49 	 0.5533319100621696 					 0.5533319100621696 


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Run Number - 6
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.40338760962919584 					 0.40338760962919584 
Iteration 1 	 0.3863827033200282 					 0.40338760962919584 
Iteration 2 	 0.3773252804644625 					 0.40338760962919584 
Iteration 3 	 0.4852616607192198 					 0.4852616607192198 
Iteration 4 	 0.44764442540594507 					 0.4852616607192198 
Iteration 5 	 0.44764442540594507 					 0.4852616607192198 
Iteration 6 	 0.49240330515892017 					 0.49240330515892017 
Iteration 7 	 0.49240330515892017 					 0.49240330515892017 
Iteration 8 	 0.49240330515892017 					 0.49240330515892017 
Iteration 9 	 0.4890293424451058 					 0.49240330515892017 
Iteration 10 	 0.5083925207889659 					 0.5083925207889659 
Iteration 11 	 0.50072076897502 					 0.5083925207889659 
Iteration 12 	 0.5135307773433996 					 0.5135307773433996 
Iteration 13 	 0.5486159011373252 					 0.5486159011373252 
Iteration 14 	 0.5677472852913446 					 0.5677472852913446 
Iteration 15 	 0.5677472852913446 					 0.5677472852913446 
Iteration 16 	 0.5684046529252416 					 0.5684046529252416 
Iteration 17 	 0.5684046529252416 					 0.5684046529252416 
Iteration 18 	 0.5677472852913446 					 0.5684046529252416 
Iteration 19 	 0.5677472852913446 					 0.5684046529252416 
Iteration 20 	 0.5677472852913446 					 0.5684046529252416 
Iteration 21 	 0.5677472852913446 					 0.5684046529252416 
Iteration 22 	 0.5677472852913446 					 0.5684046529252416 
Iteration 23 	 0.5677472852913446 					 0.5684046529252416 
Iteration 24 	 0.5677472852913446 					 0.5684046529252416 
Iteration 25 	 0.5677472852913446 					 0.5684046529252416 
Iteration 26 	 0.5677472852913446 					 0.5684046529252416 
Iteration 27 	 0.5677472852913446 					 0.5684046529252416 
Iteration 28 	 0.5677472852913446 					 0.5684046529252416 
Iteration 29 	 0.5677472852913446 					 0.5684046529252416 
Iteration 30 	 0.5677472852913446 					 0.5684046529252416 
Iteration 31 	 0.5677472852913446 					 0.5684046529252416 
Iteration 32 	 0.5677472852913446 					 0.5684046529252416 
Iteration 33 	 0.5677472852913446 					 0.5684046529252416 
Iteration 34 	 0.5677472852913446 					 0.5684046529252416 
Iteration 35 	 0.5677472852913446 					 0.5684046529252416 
Iteration 36 	 0.5677472852913446 					 0.5684046529252416 
Iteration 37 	 0.5677472852913446 					 0.5684046529252416 
Iteration 38 	 0.5677472852913446 					 0.5684046529252416 
Iteration 39 	 0.5677472852913446 					 0.5684046529252416 
Iteration 40 	 0.5677472852913446 					 0.5684046529252416 
Iteration 41 	 0.5677472852913446 					 0.5684046529252416 
Iteration 42 	 0.5677472852913446 					 0.5684046529252416 
Iteration 43 	 0.5677472852913446 					 0.5684046529252416 
Iteration 44 	 0.5677472852913446 					 0.5684046529252416 
Iteration 45 	 0.5677472852913446 					 0.5684046529252416 
Iteration 46 	 0.5677472852913446 					 0.5684046529252416 
Iteration 47 	 0.5677472852913446 					 0.5684046529252416 
Iteration 48 	 0.5677472852913446 					 0.5684046529252416 
Iteration 49 	 0.5677472852913446 					 0.5684046529252416 


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Run Number - 7
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.42342139004811735 					 0.42342139004811735 
Iteration 1 	 0.46609728031967024 					 0.46609728031967024 
Iteration 2 	 0.4655018701923982 					 0.46609728031967024 
Iteration 3 	 0.4945836232614209 					 0.4945836232614209 
Iteration 4 	 0.47954627215004736 					 0.4945836232614209 
Iteration 5 	 0.47954627215004736 					 0.4945836232614209 
Iteration 6 	 0.47954627215004736 					 0.4945836232614209 
Iteration 7 	 0.47954627215004736 					 0.4945836232614209 
Iteration 8 	 0.47954627215004736 					 0.4945836232614209 
Iteration 9 	 0.4800079470980371 					 0.4945836232614209 
Iteration 10 	 0.4800079470980371 					 0.4945836232614209 
Iteration 11 	 0.4800079470980371 					 0.4945836232614209 
Iteration 12 	 0.4800079470980371 					 0.4945836232614209 
Iteration 13 	 0.4800079470980371 					 0.4945836232614209 
Iteration 14 	 0.4800079470980371 					 0.4945836232614209 
Iteration 15 	 0.4800079470980371 					 0.4945836232614209 
Iteration 16 	 0.4800079470980371 					 0.4945836232614209 
Iteration 17 	 0.4800079470980371 					 0.4945836232614209 
Iteration 18 	 0.4800079470980371 					 0.4945836232614209 
Iteration 19 	 0.4800079470980371 					 0.4945836232614209 
Iteration 20 	 0.4800079470980371 					 0.4945836232614209 
Iteration 21 	 0.4800079470980371 					 0.4945836232614209 
Iteration 22 	 0.4800079470980371 					 0.4945836232614209 
Iteration 23 	 0.4800079470980371 					 0.4945836232614209 
Iteration 24 	 0.4800079470980371 					 0.4945836232614209 
Iteration 25 	 0.4800079470980371 					 0.4945836232614209 
Iteration 26 	 0.4800079470980371 					 0.4945836232614209 
Iteration 27 	 0.4800079470980371 					 0.4945836232614209 
Iteration 28 	 0.4800079470980371 					 0.4945836232614209 
Iteration 29 	 0.4800079470980371 					 0.4945836232614209 
Iteration 30 	 0.4800079470980371 					 0.4945836232614209 
Iteration 31 	 0.4800079470980371 					 0.4945836232614209 
Iteration 32 	 0.4800079470980371 					 0.4945836232614209 
Iteration 33 	 0.4800079470980371 					 0.4945836232614209 
Iteration 34 	 0.4800079470980371 					 0.4945836232614209 
Iteration 35 	 0.4800079470980371 					 0.4945836232614209 
Iteration 36 	 0.4800079470980371 					 0.4945836232614209 
Iteration 37 	 0.4800079470980371 					 0.4945836232614209 
Iteration 38 	 0.4800079470980371 					 0.4945836232614209 
Iteration 39 	 0.4800079470980371 					 0.4945836232614209 
Iteration 40 	 0.4800079470980371 					 0.4945836232614209 
Iteration 41 	 0.4800079470980371 					 0.4945836232614209 
Iteration 42 	 0.4800079470980371 					 0.4945836232614209 
Iteration 43 	 0.4800079470980371 					 0.4945836232614209 
Iteration 44 	 0.4800079470980371 					 0.4945836232614209 
Iteration 45 	 0.4800079470980371 					 0.4945836232614209 
Iteration 46 	 0.4800079470980371 					 0.4945836232614209 
Iteration 47 	 0.4800079470980371 					 0.4945836232614209 
Iteration 48 	 0.4800079470980371 					 0.4945836232614209 
Iteration 49 	 0.4800079470980371 					 0.4945836232614209 


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Run Number - 8
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.2892249962590021 					 0.2892249962590021 
Iteration 1 	 0.3963672971669797 					 0.3963672971669797 
Iteration 2 	 0.4765211835148859 					 0.4765211835148859 
Iteration 3 	 0.45216713802859215 					 0.4765211835148859 
Iteration 4 	 0.4765211835148859 					 0.4765211835148859 
Iteration 5 	 0.4765211835148859 					 0.4765211835148859 
Iteration 6 	 0.48347560218656715 					 0.48347560218656715 
Iteration 7 	 0.48700641882956985 					 0.48700641882956985 
Iteration 8 	 0.4844512430876615 					 0.48700641882956985 
Iteration 9 	 0.4834979393423052 					 0.48700641882956985 
Iteration 10 	 0.4646317964382835 					 0.48700641882956985 
Iteration 11 	 0.4646317964382835 					 0.48700641882956985 
Iteration 12 	 0.4800681534447995 					 0.48700641882956985 
Iteration 13 	 0.46991762322912917 					 0.48700641882956985 
Iteration 14 	 0.4804804883405646 					 0.48700641882956985 
Iteration 15 	 0.4804804883405646 					 0.48700641882956985 
Iteration 16 	 0.4804804883405646 					 0.48700641882956985 
Iteration 17 	 0.4804804883405646 					 0.48700641882956985 
Iteration 18 	 0.4804804883405646 					 0.48700641882956985 
Iteration 19 	 0.4804804883405646 					 0.48700641882956985 
Iteration 20 	 0.4804804883405646 					 0.48700641882956985 
Iteration 21 	 0.4804804883405646 					 0.48700641882956985 
Iteration 22 	 0.4804804883405646 					 0.48700641882956985 
Iteration 23 	 0.4804804883405646 					 0.48700641882956985 
Iteration 24 	 0.4804804883405646 					 0.48700641882956985 
Iteration 25 	 0.4804804883405646 					 0.48700641882956985 
Iteration 26 	 0.4804804883405646 					 0.48700641882956985 
Iteration 27 	 0.4804804883405646 					 0.48700641882956985 
Iteration 28 	 0.4804804883405646 					 0.48700641882956985 
Iteration 29 	 0.4804804883405646 					 0.48700641882956985 
Iteration 30 	 0.4804804883405646 					 0.48700641882956985 
Iteration 31 	 0.4804804883405646 					 0.48700641882956985 
Iteration 32 	 0.4804804883405646 					 0.48700641882956985 
Iteration 33 	 0.4804804883405646 					 0.48700641882956985 
Iteration 34 	 0.4804804883405646 					 0.48700641882956985 
Iteration 35 	 0.4804804883405646 					 0.48700641882956985 
Iteration 36 	 0.4804804883405646 					 0.48700641882956985 
Iteration 37 	 0.4804804883405646 					 0.48700641882956985 
Iteration 38 	 0.4804804883405646 					 0.48700641882956985 
Iteration 39 	 0.4804804883405646 					 0.48700641882956985 
Iteration 40 	 0.4804804883405646 					 0.48700641882956985 
Iteration 41 	 0.4804804883405646 					 0.48700641882956985 
Iteration 42 	 0.4804804883405646 					 0.48700641882956985 
Iteration 43 	 0.4804804883405646 					 0.48700641882956985 
Iteration 44 	 0.4804804883405646 					 0.48700641882956985 
Iteration 45 	 0.4804804883405646 					 0.48700641882956985 
Iteration 46 	 0.4804804883405646 					 0.48700641882956985 
Iteration 47 	 0.4804804883405646 					 0.48700641882956985 
Iteration 48 	 0.4804804883405646 					 0.48700641882956985 
Iteration 49 	 0.4804804883405646 					 0.48700641882956985 


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Run Number - 9
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4695674783318805 					 0.4695674783318805 
Iteration 1 	 0.3345058873041817 					 0.4695674783318805 
Iteration 2 	 0.443988098721714 					 0.4695674783318805 
Iteration 3 	 0.42545510287119903 					 0.4695674783318805 
Iteration 4 	 0.42545510287119903 					 0.4695674783318805 
Iteration 5 	 0.4275938439575116 					 0.4695674783318805 
Iteration 6 	 0.4275938439575116 					 0.4695674783318805 
Iteration 7 	 0.4275938439575116 					 0.4695674783318805 
Iteration 8 	 0.4275938439575116 					 0.4695674783318805 
Iteration 9 	 0.4275938439575116 					 0.4695674783318805 
Iteration 10 	 0.4275938439575116 					 0.4695674783318805 
Iteration 11 	 0.4275938439575116 					 0.4695674783318805 
Iteration 12 	 0.4275938439575116 					 0.4695674783318805 
Iteration 13 	 0.4275938439575116 					 0.4695674783318805 
Iteration 14 	 0.4275938439575116 					 0.4695674783318805 
Iteration 15 	 0.4275938439575116 					 0.4695674783318805 
Iteration 16 	 0.4275938439575116 					 0.4695674783318805 
Iteration 17 	 0.4275938439575116 					 0.4695674783318805 
Iteration 18 	 0.4275938439575116 					 0.4695674783318805 
Iteration 19 	 0.4275938439575116 					 0.4695674783318805 
Iteration 20 	 0.4275938439575116 					 0.4695674783318805 
Iteration 21 	 0.4275938439575116 					 0.4695674783318805 
Iteration 22 	 0.4275938439575116 					 0.4695674783318805 
Iteration 23 	 0.4275938439575116 					 0.4695674783318805 
Iteration 24 	 0.4275938439575116 					 0.4695674783318805 
Iteration 25 	 0.4275938439575116 					 0.4695674783318805 
Iteration 26 	 0.4275938439575116 					 0.4695674783318805 
Iteration 27 	 0.4275938439575116 					 0.4695674783318805 
Iteration 28 	 0.4275938439575116 					 0.4695674783318805 
Iteration 29 	 0.4275938439575116 					 0.4695674783318805 
Iteration 30 	 0.4275938439575116 					 0.4695674783318805 
Iteration 31 	 0.4275938439575116 					 0.4695674783318805 
Iteration 32 	 0.4275938439575116 					 0.4695674783318805 
Iteration 33 	 0.4275938439575116 					 0.4695674783318805 
Iteration 34 	 0.4275938439575116 					 0.4695674783318805 
Iteration 35 	 0.4275938439575116 					 0.4695674783318805 
Iteration 36 	 0.4275938439575116 					 0.4695674783318805 
Iteration 37 	 0.4275938439575116 					 0.4695674783318805 
Iteration 38 	 0.4275938439575116 					 0.4695674783318805 
Iteration 39 	 0.4275938439575116 					 0.4695674783318805 
Iteration 40 	 0.4275938439575116 					 0.4695674783318805 
Iteration 41 	 0.4275938439575116 					 0.4695674783318805 
Iteration 42 	 0.4275938439575116 					 0.4695674783318805 
Iteration 43 	 0.4275938439575116 					 0.4695674783318805 
Iteration 44 	 0.4275938439575116 					 0.4695674783318805 
Iteration 45 	 0.4275938439575116 					 0.4695674783318805 
Iteration 46 	 0.4275938439575116 					 0.4695674783318805 
Iteration 47 	 0.4275938439575116 					 0.4695674783318805 
Iteration 48 	 0.4275938439575116 					 0.4695674783318805 
Iteration 49 	 0.4275938439575116 					 0.4695674783318805 


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Run Number - 10
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.45496712495920943 					 0.45496712495920943 
Iteration 1 	 0.4399684040987949 					 0.45496712495920943 
Iteration 2 	 0.4255456767921433 					 0.45496712495920943 
Iteration 3 	 0.48726628412324546 					 0.48726628412324546 
Iteration 4 	 0.48922070984335864 					 0.48922070984335864 
Iteration 5 	 0.5075731668475026 					 0.5075731668475026 
Iteration 6 	 0.5054831018341981 					 0.5075731668475026 
Iteration 7 	 0.5273075627440471 					 0.5273075627440471 
Iteration 8 	 0.5173393009223001 					 0.5273075627440471 
Iteration 9 	 0.537116043078468 					 0.537116043078468 
Iteration 10 	 0.537116043078468 					 0.537116043078468 
Iteration 11 	 0.537116043078468 					 0.537116043078468 
Iteration 12 	 0.537116043078468 					 0.537116043078468 
Iteration 13 	 0.5373702219759152 					 0.5373702219759152 
Iteration 14 	 0.5377559661821047 					 0.5377559661821047 
Iteration 15 	 0.5377559661821047 					 0.5377559661821047 
Iteration 16 	 0.5377559661821047 					 0.5377559661821047 
Iteration 17 	 0.5377559661821047 					 0.5377559661821047 
Iteration 18 	 0.5377559661821047 					 0.5377559661821047 
Iteration 19 	 0.5377559661821047 					 0.5377559661821047 
Iteration 20 	 0.5377559661821047 					 0.5377559661821047 
Iteration 21 	 0.5377559661821047 					 0.5377559661821047 
Iteration 22 	 0.5377559661821047 					 0.5377559661821047 
Iteration 23 	 0.5377559661821047 					 0.5377559661821047 
Iteration 24 	 0.5377559661821047 					 0.5377559661821047 
Iteration 25 	 0.5377559661821047 					 0.5377559661821047 
Iteration 26 	 0.5377559661821047 					 0.5377559661821047 
Iteration 27 	 0.5377559661821047 					 0.5377559661821047 
Iteration 28 	 0.5377559661821047 					 0.5377559661821047 
Iteration 29 	 0.5377559661821047 					 0.5377559661821047 
Iteration 30 	 0.5377559661821047 					 0.5377559661821047 
Iteration 31 	 0.5377559661821047 					 0.5377559661821047 
Iteration 32 	 0.5377559661821047 					 0.5377559661821047 
Iteration 33 	 0.5377559661821047 					 0.5377559661821047 
Iteration 34 	 0.5377559661821047 					 0.5377559661821047 
Iteration 35 	 0.5377559661821047 					 0.5377559661821047 
Iteration 36 	 0.5377559661821047 					 0.5377559661821047 
Iteration 37 	 0.5377559661821047 					 0.5377559661821047 
Iteration 38 	 0.5377559661821047 					 0.5377559661821047 
Iteration 39 	 0.5377559661821047 					 0.5377559661821047 
Iteration 40 	 0.5377559661821047 					 0.5377559661821047 
Iteration 41 	 0.5377559661821047 					 0.5377559661821047 
Iteration 42 	 0.5377559661821047 					 0.5377559661821047 
Iteration 43 	 0.5377559661821047 					 0.5377559661821047 
Iteration 44 	 0.5377559661821047 					 0.5377559661821047 
Iteration 45 	 0.5377559661821047 					 0.5377559661821047 
Iteration 46 	 0.5377559661821047 					 0.5377559661821047 
Iteration 47 	 0.5377559661821047 					 0.5377559661821047 
Iteration 48 	 0.5377559661821047 					 0.5377559661821047 
Iteration 49 	 0.5377559661821047 					 0.5377559661821047 


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Run Number - 11
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4129974274603031 					 0.4129974274603031 
Iteration 1 	 0.4311175356159076 					 0.4311175356159076 
Iteration 2 	 0.4784919281150526 					 0.4784919281150526 
Iteration 3 	 0.49990941047206805 					 0.49990941047206805 
Iteration 4 	 0.49664629546148886 					 0.49990941047206805 
Iteration 5 	 0.49847097888424163 					 0.49990941047206805 
Iteration 6 	 0.49664629546148886 					 0.49990941047206805 
Iteration 7 	 0.5024776298399913 					 0.5024776298399913 
Iteration 8 	 0.5080804972554748 					 0.5080804972554748 
Iteration 9 	 0.5244511978593637 					 0.5244511978593637 
Iteration 10 	 0.5244511978593637 					 0.5244511978593637 
Iteration 11 	 0.5244511978593637 					 0.5244511978593637 
Iteration 12 	 0.5220613036611035 					 0.5244511978593637 
Iteration 13 	 0.5301587278931013 					 0.5301587278931013 
Iteration 14 	 0.5310042613196464 					 0.5310042613196464 
Iteration 15 	 0.5310042613196464 					 0.5310042613196464 
Iteration 16 	 0.5310042613196464 					 0.5310042613196464 
Iteration 17 	 0.5310042613196464 					 0.5310042613196464 
Iteration 18 	 0.5310042613196464 					 0.5310042613196464 
Iteration 19 	 0.5310042613196464 					 0.5310042613196464 
Iteration 20 	 0.5310042613196464 					 0.5310042613196464 
Iteration 21 	 0.5310042613196464 					 0.5310042613196464 
Iteration 22 	 0.5310042613196464 					 0.5310042613196464 
Iteration 23 	 0.5310042613196464 					 0.5310042613196464 
Iteration 24 	 0.5310042613196464 					 0.5310042613196464 
Iteration 25 	 0.5310042613196464 					 0.5310042613196464 
Iteration 26 	 0.5310042613196464 					 0.5310042613196464 
Iteration 27 	 0.5310042613196464 					 0.5310042613196464 
Iteration 28 	 0.5310042613196464 					 0.5310042613196464 
Iteration 29 	 0.5310042613196464 					 0.5310042613196464 
Iteration 30 	 0.5310042613196464 					 0.5310042613196464 
Iteration 31 	 0.5310042613196464 					 0.5310042613196464 
Iteration 32 	 0.5310042613196464 					 0.5310042613196464 
Iteration 33 	 0.5310042613196464 					 0.5310042613196464 
Iteration 34 	 0.5310042613196464 					 0.5310042613196464 
Iteration 35 	 0.5310042613196464 					 0.5310042613196464 
Iteration 36 	 0.5310042613196464 					 0.5310042613196464 
Iteration 37 	 0.5310042613196464 					 0.5310042613196464 
Iteration 38 	 0.5310042613196464 					 0.5310042613196464 
Iteration 39 	 0.5310042613196464 					 0.5310042613196464 
Iteration 40 	 0.5310042613196464 					 0.5310042613196464 
Iteration 41 	 0.5310042613196464 					 0.5310042613196464 
Iteration 42 	 0.5310042613196464 					 0.5310042613196464 
Iteration 43 	 0.5310042613196464 					 0.5310042613196464 
Iteration 44 	 0.5310042613196464 					 0.5310042613196464 
Iteration 45 	 0.5310042613196464 					 0.5310042613196464 
Iteration 46 	 0.5310042613196464 					 0.5310042613196464 
Iteration 47 	 0.5310042613196464 					 0.5310042613196464 
Iteration 48 	 0.5310042613196464 					 0.5310042613196464 
Iteration 49 	 0.5310042613196464 					 0.5310042613196464 


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Run Number - 12
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.38594954803114045 					 0.38594954803114045 
Iteration 1 	 0.47578394912828925 					 0.47578394912828925 
Iteration 2 	 0.5165068263229066 					 0.5165068263229066 
Iteration 3 	 0.5165068263229066 					 0.5165068263229066 
Iteration 4 	 0.5141348617391072 					 0.5165068263229066 
Iteration 5 	 0.5093932984908807 					 0.5165068263229066 
Iteration 6 	 0.4888252667989546 					 0.5165068263229066 
Iteration 7 	 0.4888252667989546 					 0.5165068263229066 
Iteration 8 	 0.5005845153776292 					 0.5165068263229066 
Iteration 9 	 0.5115035554694737 					 0.5165068263229066 
Iteration 10 	 0.5142776315954788 					 0.5165068263229066 
Iteration 11 	 0.5115035554694737 					 0.5165068263229066 
Iteration 12 	 0.5049462431136852 					 0.5165068263229066 
Iteration 13 	 0.4917149318379719 					 0.5165068263229066 
Iteration 14 	 0.5115035554694737 					 0.5165068263229066 
Iteration 15 	 0.4917149318379719 					 0.5165068263229066 
Iteration 16 	 0.4917149318379719 					 0.5165068263229066 
Iteration 17 	 0.49289446721677643 					 0.5165068263229066 
Iteration 18 	 0.5060652445455511 					 0.5165068263229066 
Iteration 19 	 0.5060652445455511 					 0.5165068263229066 
Iteration 20 	 0.5156147116237654 					 0.5165068263229066 
Iteration 21 	 0.5156147116237654 					 0.5165068263229066 
Iteration 22 	 0.5156147116237654 					 0.5165068263229066 
Iteration 23 	 0.5156147116237654 					 0.5165068263229066 
Iteration 24 	 0.5156147116237654 					 0.5165068263229066 
Iteration 25 	 0.5156147116237654 					 0.5165068263229066 
Iteration 26 	 0.5156147116237654 					 0.5165068263229066 
Iteration 27 	 0.5156147116237654 					 0.5165068263229066 
Iteration 28 	 0.5156147116237654 					 0.5165068263229066 
Iteration 29 	 0.5156147116237654 					 0.5165068263229066 
Iteration 30 	 0.5156147116237654 					 0.5165068263229066 
Iteration 31 	 0.5156147116237654 					 0.5165068263229066 
Iteration 32 	 0.5156147116237654 					 0.5165068263229066 
Iteration 33 	 0.5156147116237654 					 0.5165068263229066 
Iteration 34 	 0.5156147116237654 					 0.5165068263229066 
Iteration 35 	 0.5156147116237654 					 0.5165068263229066 
Iteration 36 	 0.5156147116237654 					 0.5165068263229066 
Iteration 37 	 0.5156147116237654 					 0.5165068263229066 
Iteration 38 	 0.5156147116237654 					 0.5165068263229066 
Iteration 39 	 0.5156147116237654 					 0.5165068263229066 
Iteration 40 	 0.5156147116237654 					 0.5165068263229066 
Iteration 41 	 0.5156147116237654 					 0.5165068263229066 
Iteration 42 	 0.5156147116237654 					 0.5165068263229066 
Iteration 43 	 0.5156147116237654 					 0.5165068263229066 
Iteration 44 	 0.5156147116237654 					 0.5165068263229066 
Iteration 45 	 0.5156147116237654 					 0.5165068263229066 
Iteration 46 	 0.5156147116237654 					 0.5165068263229066 
Iteration 47 	 0.5156147116237654 					 0.5165068263229066 
Iteration 48 	 0.5156147116237654 					 0.5165068263229066 
Iteration 49 	 0.5156147116237654 					 0.5165068263229066 


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Run Number - 13
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4761332854567636 					 0.4761332854567636 
Iteration 1 	 0.4926666161526149 					 0.4926666161526149 
Iteration 2 	 0.41893419963223 					 0.4926666161526149 
Iteration 3 	 0.47657884738181744 					 0.4926666161526149 
Iteration 4 	 0.47657884738181744 					 0.4926666161526149 
Iteration 5 	 0.5077037183166339 					 0.5077037183166339 
Iteration 6 	 0.5077037183166339 					 0.5077037183166339 
Iteration 7 	 0.5077037183166339 					 0.5077037183166339 
Iteration 8 	 0.5160724263404434 					 0.5160724263404434 
Iteration 9 	 0.5160724263404434 					 0.5160724263404434 
Iteration 10 	 0.501366065596044 					 0.5160724263404434 
Iteration 11 	 0.501366065596044 					 0.5160724263404434 
Iteration 12 	 0.501366065596044 					 0.5160724263404434 
Iteration 13 	 0.501366065596044 					 0.5160724263404434 
Iteration 14 	 0.501366065596044 					 0.5160724263404434 
Iteration 15 	 0.501366065596044 					 0.5160724263404434 
Iteration 16 	 0.501366065596044 					 0.5160724263404434 
Iteration 17 	 0.501366065596044 					 0.5160724263404434 
Iteration 18 	 0.501366065596044 					 0.5160724263404434 
Iteration 19 	 0.501366065596044 					 0.5160724263404434 
Iteration 20 	 0.501366065596044 					 0.5160724263404434 
Iteration 21 	 0.501366065596044 					 0.5160724263404434 
Iteration 22 	 0.501366065596044 					 0.5160724263404434 
Iteration 23 	 0.501366065596044 					 0.5160724263404434 
Iteration 24 	 0.501366065596044 					 0.5160724263404434 
Iteration 25 	 0.501366065596044 					 0.5160724263404434 
Iteration 26 	 0.501366065596044 					 0.5160724263404434 
Iteration 27 	 0.501366065596044 					 0.5160724263404434 
Iteration 28 	 0.501366065596044 					 0.5160724263404434 
Iteration 29 	 0.501366065596044 					 0.5160724263404434 
Iteration 30 	 0.501366065596044 					 0.5160724263404434 
Iteration 31 	 0.501366065596044 					 0.5160724263404434 
Iteration 32 	 0.501366065596044 					 0.5160724263404434 
Iteration 33 	 0.501366065596044 					 0.5160724263404434 
Iteration 34 	 0.501366065596044 					 0.5160724263404434 
Iteration 35 	 0.501366065596044 					 0.5160724263404434 
Iteration 36 	 0.501366065596044 					 0.5160724263404434 
Iteration 37 	 0.501366065596044 					 0.5160724263404434 
Iteration 38 	 0.501366065596044 					 0.5160724263404434 
Iteration 39 	 0.501366065596044 					 0.5160724263404434 
Iteration 40 	 0.501366065596044 					 0.5160724263404434 
Iteration 41 	 0.501366065596044 					 0.5160724263404434 
Iteration 42 	 0.501366065596044 					 0.5160724263404434 
Iteration 43 	 0.501366065596044 					 0.5160724263404434 
Iteration 44 	 0.501366065596044 					 0.5160724263404434 
Iteration 45 	 0.501366065596044 					 0.5160724263404434 
Iteration 46 	 0.501366065596044 					 0.5160724263404434 
Iteration 47 	 0.501366065596044 					 0.5160724263404434 
Iteration 48 	 0.501366065596044 					 0.5160724263404434 
Iteration 49 	 0.501366065596044 					 0.5160724263404434 


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Run Number - 14
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5025397524235478 					 0.5025397524235478 
Iteration 1 	 0.5523278242469213 					 0.5523278242469213 
Iteration 2 	 0.5523278242469213 					 0.5523278242469213 
Iteration 3 	 0.5308837025483161 					 0.5523278242469213 
Iteration 4 	 0.5306275287938261 					 0.5523278242469213 
Iteration 5 	 0.4955204800317871 					 0.5523278242469213 
Iteration 6 	 0.5273174128887111 					 0.5523278242469213 
Iteration 7 	 0.48548055211761326 					 0.5523278242469213 
Iteration 8 	 0.5046978917621405 					 0.5523278242469213 
Iteration 9 	 0.5169740904617216 					 0.5523278242469213 
Iteration 10 	 0.5171224562663217 					 0.5523278242469213 
Iteration 11 	 0.5153917649416747 					 0.5523278242469213 
Iteration 12 	 0.5379644024450111 					 0.5523278242469213 
Iteration 13 	 0.5256313407549646 					 0.5523278242469213 
Iteration 14 	 0.5256313407549646 					 0.5523278242469213 
Iteration 15 	 0.5261347807185109 					 0.5523278242469213 
Iteration 16 	 0.5261347807185109 					 0.5523278242469213 
Iteration 17 	 0.5340831706252777 					 0.5523278242469213 
Iteration 18 	 0.5340831706252777 					 0.5523278242469213 
Iteration 19 	 0.5340831706252777 					 0.5523278242469213 
Iteration 20 	 0.5340831706252777 					 0.5523278242469213 
Iteration 21 	 0.5340831706252777 					 0.5523278242469213 
Iteration 22 	 0.5340831706252777 					 0.5523278242469213 
Iteration 23 	 0.5340831706252777 					 0.5523278242469213 
Iteration 24 	 0.5340831706252777 					 0.5523278242469213 
Iteration 25 	 0.5340831706252777 					 0.5523278242469213 
Iteration 26 	 0.5340831706252777 					 0.5523278242469213 
Iteration 27 	 0.5340831706252777 					 0.5523278242469213 
Iteration 28 	 0.5340831706252777 					 0.5523278242469213 
Iteration 29 	 0.5340831706252777 					 0.5523278242469213 
Iteration 30 	 0.5340831706252777 					 0.5523278242469213 
Iteration 31 	 0.5340831706252777 					 0.5523278242469213 
Iteration 32 	 0.5340831706252777 					 0.5523278242469213 
Iteration 33 	 0.5340831706252777 					 0.5523278242469213 
Iteration 34 	 0.5340831706252777 					 0.5523278242469213 
Iteration 35 	 0.5340831706252777 					 0.5523278242469213 
Iteration 36 	 0.5340831706252777 					 0.5523278242469213 
Iteration 37 	 0.5340831706252777 					 0.5523278242469213 
Iteration 38 	 0.5340831706252777 					 0.5523278242469213 
Iteration 39 	 0.5340831706252777 					 0.5523278242469213 
Iteration 40 	 0.5340831706252777 					 0.5523278242469213 
Iteration 41 	 0.5340831706252777 					 0.5523278242469213 
Iteration 42 	 0.5340831706252777 					 0.5523278242469213 
Iteration 43 	 0.5340831706252777 					 0.5523278242469213 
Iteration 44 	 0.5340831706252777 					 0.5523278242469213 
Iteration 45 	 0.5340831706252777 					 0.5523278242469213 
Iteration 46 	 0.5340831706252777 					 0.5523278242469213 
Iteration 47 	 0.5340831706252777 					 0.5523278242469213 
Iteration 48 	 0.5340831706252777 					 0.5523278242469213 
Iteration 49 	 0.5340831706252777 					 0.5523278242469213 


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Run Number - 15
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.46572401004692987 					 0.46572401004692987 
Iteration 1 	 0.39059575618884235 					 0.46572401004692987 
Iteration 2 	 0.4348169649267238 					 0.46572401004692987 
Iteration 3 	 0.45838548945436886 					 0.46572401004692987 
Iteration 4 	 0.45838548945436886 					 0.46572401004692987 
Iteration 5 	 0.45838548945436886 					 0.46572401004692987 
Iteration 6 	 0.45838548945436886 					 0.46572401004692987 
Iteration 7 	 0.45838548945436886 					 0.46572401004692987 
Iteration 8 	 0.45838548945436886 					 0.46572401004692987 
Iteration 9 	 0.45838548945436886 					 0.46572401004692987 
Iteration 10 	 0.45838548945436886 					 0.46572401004692987 
Iteration 11 	 0.45838548945436886 					 0.46572401004692987 
Iteration 12 	 0.45838548945436886 					 0.46572401004692987 
Iteration 13 	 0.45838548945436886 					 0.46572401004692987 
Iteration 14 	 0.45838548945436886 					 0.46572401004692987 
Iteration 15 	 0.45838548945436886 					 0.46572401004692987 
Iteration 16 	 0.45838548945436886 					 0.46572401004692987 
Iteration 17 	 0.45838548945436886 					 0.46572401004692987 
Iteration 18 	 0.45838548945436886 					 0.46572401004692987 
Iteration 19 	 0.45838548945436886 					 0.46572401004692987 
Iteration 20 	 0.45838548945436886 					 0.46572401004692987 
Iteration 21 	 0.45838548945436886 					 0.46572401004692987 
Iteration 22 	 0.45838548945436886 					 0.46572401004692987 
Iteration 23 	 0.45838548945436886 					 0.46572401004692987 
Iteration 24 	 0.45838548945436886 					 0.46572401004692987 
Iteration 25 	 0.45838548945436886 					 0.46572401004692987 
Iteration 26 	 0.45838548945436886 					 0.46572401004692987 
Iteration 27 	 0.45838548945436886 					 0.46572401004692987 
Iteration 28 	 0.45838548945436886 					 0.46572401004692987 
Iteration 29 	 0.45838548945436886 					 0.46572401004692987 
Iteration 30 	 0.45838548945436886 					 0.46572401004692987 
Iteration 31 	 0.45838548945436886 					 0.46572401004692987 
Iteration 32 	 0.45838548945436886 					 0.46572401004692987 
Iteration 33 	 0.45838548945436886 					 0.46572401004692987 
Iteration 34 	 0.45838548945436886 					 0.46572401004692987 
Iteration 35 	 0.45838548945436886 					 0.46572401004692987 
Iteration 36 	 0.45838548945436886 					 0.46572401004692987 
Iteration 37 	 0.45838548945436886 					 0.46572401004692987 
Iteration 38 	 0.45838548945436886 					 0.46572401004692987 
Iteration 39 	 0.45838548945436886 					 0.46572401004692987 
Iteration 40 	 0.45838548945436886 					 0.46572401004692987 
Iteration 41 	 0.45838548945436886 					 0.46572401004692987 
Iteration 42 	 0.45838548945436886 					 0.46572401004692987 
Iteration 43 	 0.45838548945436886 					 0.46572401004692987 
Iteration 44 	 0.45838548945436886 					 0.46572401004692987 
Iteration 45 	 0.45838548945436886 					 0.46572401004692987 
Iteration 46 	 0.45838548945436886 					 0.46572401004692987 
Iteration 47 	 0.45838548945436886 					 0.46572401004692987 
Iteration 48 	 0.45838548945436886 					 0.46572401004692987 
Iteration 49 	 0.45838548945436886 					 0.46572401004692987 


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Run Number - 16
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.31328127246906035 					 0.31328127246906035 
Iteration 1 	 0.45204440086930403 					 0.45204440086930403 
Iteration 2 	 0.45638800748010777 					 0.45638800748010777 
Iteration 3 	 0.45204440086930403 					 0.45638800748010777 
Iteration 4 	 0.47492135295630084 					 0.47492135295630084 
Iteration 5 	 0.46275699267961923 					 0.47492135295630084 
Iteration 6 	 0.4378948854090823 					 0.47492135295630084 
Iteration 7 	 0.4846738550493248 					 0.4846738550493248 
Iteration 8 	 0.4782475065267715 					 0.4846738550493248 
Iteration 9 	 0.4846738550493248 					 0.4846738550493248 
Iteration 10 	 0.49534510226629125 					 0.49534510226629125 
Iteration 11 	 0.49534510226629125 					 0.49534510226629125 
Iteration 12 	 0.49534510226629125 					 0.49534510226629125 
Iteration 13 	 0.49534510226629125 					 0.49534510226629125 
Iteration 14 	 0.49534510226629125 					 0.49534510226629125 
Iteration 15 	 0.49534510226629125 					 0.49534510226629125 
Iteration 16 	 0.49534510226629125 					 0.49534510226629125 
Iteration 17 	 0.49534510226629125 					 0.49534510226629125 
Iteration 18 	 0.49534510226629125 					 0.49534510226629125 
Iteration 19 	 0.49534510226629125 					 0.49534510226629125 
Iteration 20 	 0.49534510226629125 					 0.49534510226629125 
Iteration 21 	 0.49534510226629125 					 0.49534510226629125 
Iteration 22 	 0.49534510226629125 					 0.49534510226629125 
Iteration 23 	 0.49534510226629125 					 0.49534510226629125 
Iteration 24 	 0.49534510226629125 					 0.49534510226629125 
Iteration 25 	 0.49534510226629125 					 0.49534510226629125 
Iteration 26 	 0.49534510226629125 					 0.49534510226629125 
Iteration 27 	 0.49534510226629125 					 0.49534510226629125 
Iteration 28 	 0.49534510226629125 					 0.49534510226629125 
Iteration 29 	 0.49534510226629125 					 0.49534510226629125 
Iteration 30 	 0.49534510226629125 					 0.49534510226629125 
Iteration 31 	 0.49534510226629125 					 0.49534510226629125 
Iteration 32 	 0.49534510226629125 					 0.49534510226629125 
Iteration 33 	 0.49534510226629125 					 0.49534510226629125 
Iteration 34 	 0.49534510226629125 					 0.49534510226629125 
Iteration 35 	 0.49534510226629125 					 0.49534510226629125 
Iteration 36 	 0.49534510226629125 					 0.49534510226629125 
Iteration 37 	 0.49534510226629125 					 0.49534510226629125 
Iteration 38 	 0.49534510226629125 					 0.49534510226629125 
Iteration 39 	 0.49534510226629125 					 0.49534510226629125 
Iteration 40 	 0.49534510226629125 					 0.49534510226629125 
Iteration 41 	 0.49534510226629125 					 0.49534510226629125 
Iteration 42 	 0.49534510226629125 					 0.49534510226629125 
Iteration 43 	 0.49534510226629125 					 0.49534510226629125 
Iteration 44 	 0.49534510226629125 					 0.49534510226629125 
Iteration 45 	 0.49534510226629125 					 0.49534510226629125 
Iteration 46 	 0.49534510226629125 					 0.49534510226629125 
Iteration 47 	 0.49534510226629125 					 0.49534510226629125 
Iteration 48 	 0.49534510226629125 					 0.49534510226629125 
Iteration 49 	 0.49534510226629125 					 0.49534510226629125 


 ----------------------------------------------------------------------------------------
Run Number - 17
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4066306900514895 					 0.4066306900514895 
Iteration 1 	 0.4785493915992106 					 0.4785493915992106 
Iteration 2 	 0.43002188163220756 					 0.4785493915992106 
Iteration 3 	 0.4508245906037853 					 0.4785493915992106 
Iteration 4 	 0.46110794125283855 					 0.4785493915992106 
Iteration 5 	 0.46110794125283855 					 0.4785493915992106 
Iteration 6 	 0.46110794125283855 					 0.4785493915992106 
Iteration 7 	 0.46110794125283855 					 0.4785493915992106 
Iteration 8 	 0.46110794125283855 					 0.4785493915992106 
Iteration 9 	 0.4712398266036234 					 0.4785493915992106 
Iteration 10 	 0.46110794125283855 					 0.4785493915992106 
Iteration 11 	 0.46110794125283855 					 0.4785493915992106 
Iteration 12 	 0.46110794125283855 					 0.4785493915992106 
Iteration 13 	 0.46110794125283855 					 0.4785493915992106 
Iteration 14 	 0.46110794125283855 					 0.4785493915992106 
Iteration 15 	 0.46110794125283855 					 0.4785493915992106 
Iteration 16 	 0.46110794125283855 					 0.4785493915992106 
Iteration 17 	 0.46110794125283855 					 0.4785493915992106 
Iteration 18 	 0.46110794125283855 					 0.4785493915992106 
Iteration 19 	 0.46110794125283855 					 0.4785493915992106 
Iteration 20 	 0.46110794125283855 					 0.4785493915992106 
Iteration 21 	 0.46110794125283855 					 0.4785493915992106 
Iteration 22 	 0.46110794125283855 					 0.4785493915992106 
Iteration 23 	 0.46110794125283855 					 0.4785493915992106 
Iteration 24 	 0.46110794125283855 					 0.4785493915992106 
Iteration 25 	 0.46110794125283855 					 0.4785493915992106 
Iteration 26 	 0.46110794125283855 					 0.4785493915992106 
Iteration 27 	 0.46110794125283855 					 0.4785493915992106 
Iteration 28 	 0.46110794125283855 					 0.4785493915992106 
Iteration 29 	 0.46110794125283855 					 0.4785493915992106 
Iteration 30 	 0.46110794125283855 					 0.4785493915992106 
Iteration 31 	 0.46110794125283855 					 0.4785493915992106 
Iteration 32 	 0.46110794125283855 					 0.4785493915992106 
Iteration 33 	 0.46110794125283855 					 0.4785493915992106 
Iteration 34 	 0.46110794125283855 					 0.4785493915992106 
Iteration 35 	 0.46110794125283855 					 0.4785493915992106 
Iteration 36 	 0.46110794125283855 					 0.4785493915992106 
Iteration 37 	 0.46110794125283855 					 0.4785493915992106 
Iteration 38 	 0.46110794125283855 					 0.4785493915992106 
Iteration 39 	 0.46110794125283855 					 0.4785493915992106 
Iteration 40 	 0.46110794125283855 					 0.4785493915992106 
Iteration 41 	 0.46110794125283855 					 0.4785493915992106 
Iteration 42 	 0.46110794125283855 					 0.4785493915992106 
Iteration 43 	 0.46110794125283855 					 0.4785493915992106 
Iteration 44 	 0.46110794125283855 					 0.4785493915992106 
Iteration 45 	 0.46110794125283855 					 0.4785493915992106 
Iteration 46 	 0.46110794125283855 					 0.4785493915992106 
Iteration 47 	 0.46110794125283855 					 0.4785493915992106 
Iteration 48 	 0.46110794125283855 					 0.4785493915992106 
Iteration 49 	 0.46110794125283855 					 0.4785493915992106 


 ----------------------------------------------------------------------------------------
Run Number - 18
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.39529726425429834 					 0.39529726425429834 
Iteration 1 	 0.40040802346555227 					 0.40040802346555227 
Iteration 2 	 0.4470972830235181 					 0.4470972830235181 
Iteration 3 	 0.447935014477927 					 0.447935014477927 
Iteration 4 	 0.5415987385946865 					 0.5415987385946865 
Iteration 5 	 0.4651550931967099 					 0.5415987385946865 
Iteration 6 	 0.4651550931967099 					 0.5415987385946865 
Iteration 7 	 0.45424347891069905 					 0.5415987385946865 
Iteration 8 	 0.4606291461891606 					 0.5415987385946865 
Iteration 9 	 0.4555286057318586 					 0.5415987385946865 
Iteration 10 	 0.45424347891069905 					 0.5415987385946865 
Iteration 11 	 0.4547258962635725 					 0.5415987385946865 
Iteration 12 	 0.45424347891069905 					 0.5415987385946865 
Iteration 13 	 0.45424347891069905 					 0.5415987385946865 
Iteration 14 	 0.4576741787925534 					 0.5415987385946865 
Iteration 15 	 0.4576741787925534 					 0.5415987385946865 
Iteration 16 	 0.4576741787925534 					 0.5415987385946865 
Iteration 17 	 0.4576741787925534 					 0.5415987385946865 
Iteration 18 	 0.4576741787925534 					 0.5415987385946865 
Iteration 19 	 0.4576741787925534 					 0.5415987385946865 
Iteration 20 	 0.4576741787925534 					 0.5415987385946865 
Iteration 21 	 0.4576741787925534 					 0.5415987385946865 
Iteration 22 	 0.4576741787925534 					 0.5415987385946865 
Iteration 23 	 0.4576741787925534 					 0.5415987385946865 
Iteration 24 	 0.4576741787925534 					 0.5415987385946865 
Iteration 25 	 0.4576741787925534 					 0.5415987385946865 
Iteration 26 	 0.4576741787925534 					 0.5415987385946865 
Iteration 27 	 0.4576741787925534 					 0.5415987385946865 
Iteration 28 	 0.4576741787925534 					 0.5415987385946865 
Iteration 29 	 0.4576741787925534 					 0.5415987385946865 
Iteration 30 	 0.4576741787925534 					 0.5415987385946865 
Iteration 31 	 0.4576741787925534 					 0.5415987385946865 
Iteration 32 	 0.4576741787925534 					 0.5415987385946865 
Iteration 33 	 0.4576741787925534 					 0.5415987385946865 
Iteration 34 	 0.4576741787925534 					 0.5415987385946865 
Iteration 35 	 0.4576741787925534 					 0.5415987385946865 
Iteration 36 	 0.4576741787925534 					 0.5415987385946865 
Iteration 37 	 0.4576741787925534 					 0.5415987385946865 
Iteration 38 	 0.4576741787925534 					 0.5415987385946865 
Iteration 39 	 0.4576741787925534 					 0.5415987385946865 
Iteration 40 	 0.4576741787925534 					 0.5415987385946865 
Iteration 41 	 0.4576741787925534 					 0.5415987385946865 
Iteration 42 	 0.4576741787925534 					 0.5415987385946865 
Iteration 43 	 0.4576741787925534 					 0.5415987385946865 
Iteration 44 	 0.4576741787925534 					 0.5415987385946865 
Iteration 45 	 0.4576741787925534 					 0.5415987385946865 
Iteration 46 	 0.4576741787925534 					 0.5415987385946865 
Iteration 47 	 0.4576741787925534 					 0.5415987385946865 
Iteration 48 	 0.4576741787925534 					 0.5415987385946865 
Iteration 49 	 0.4576741787925534 					 0.5415987385946865 


 ----------------------------------------------------------------------------------------
Run Number - 19
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4999420135721861 					 0.4999420135721861 
Iteration 1 	 0.43429821383444484 					 0.4999420135721861 
Iteration 2 	 0.5375881094460082 					 0.5375881094460082 
Iteration 3 	 0.5375881094460082 					 0.5375881094460082 
Iteration 4 	 0.49130638928280823 					 0.5375881094460082 
Iteration 5 	 0.4961110923128492 					 0.5375881094460082 
Iteration 6 	 0.5264364034250688 					 0.5375881094460082 
Iteration 7 	 0.5245870553333949 					 0.5375881094460082 
Iteration 8 	 0.5210051930651387 					 0.5375881094460082 
Iteration 9 	 0.5594917612984307 					 0.5594917612984307 
Iteration 10 	 0.5594917612984307 					 0.5594917612984307 
Iteration 11 	 0.5624995121567982 					 0.5624995121567982 
Iteration 12 	 0.5624995121567982 					 0.5624995121567982 
Iteration 13 	 0.5624995121567982 					 0.5624995121567982 
Iteration 14 	 0.5624995121567982 					 0.5624995121567982 
Iteration 15 	 0.5624995121567982 					 0.5624995121567982 
Iteration 16 	 0.5624995121567982 					 0.5624995121567982 
Iteration 17 	 0.5624995121567982 					 0.5624995121567982 
Iteration 18 	 0.5624995121567982 					 0.5624995121567982 
Iteration 19 	 0.5624995121567982 					 0.5624995121567982 
Iteration 20 	 0.5624995121567982 					 0.5624995121567982 
Iteration 21 	 0.5624995121567982 					 0.5624995121567982 
Iteration 22 	 0.5624995121567982 					 0.5624995121567982 
Iteration 23 	 0.5624995121567982 					 0.5624995121567982 
Iteration 24 	 0.5624995121567982 					 0.5624995121567982 
Iteration 25 	 0.5624995121567982 					 0.5624995121567982 
Iteration 26 	 0.5624995121567982 					 0.5624995121567982 
Iteration 27 	 0.5624995121567982 					 0.5624995121567982 
Iteration 28 	 0.5624995121567982 					 0.5624995121567982 
Iteration 29 	 0.5624995121567982 					 0.5624995121567982 
Iteration 30 	 0.5624995121567982 					 0.5624995121567982 
Iteration 31 	 0.5624995121567982 					 0.5624995121567982 
Iteration 32 	 0.5624995121567982 					 0.5624995121567982 
Iteration 33 	 0.5624995121567982 					 0.5624995121567982 
Iteration 34 	 0.5624995121567982 					 0.5624995121567982 
Iteration 35 	 0.5624995121567982 					 0.5624995121567982 
Iteration 36 	 0.5624995121567982 					 0.5624995121567982 
Iteration 37 	 0.5624995121567982 					 0.5624995121567982 
Iteration 38 	 0.5624995121567982 					 0.5624995121567982 
Iteration 39 	 0.5624995121567982 					 0.5624995121567982 
Iteration 40 	 0.5624995121567982 					 0.5624995121567982 
Iteration 41 	 0.5624995121567982 					 0.5624995121567982 
Iteration 42 	 0.5624995121567982 					 0.5624995121567982 
Iteration 43 	 0.5624995121567982 					 0.5624995121567982 
Iteration 44 	 0.5624995121567982 					 0.5624995121567982 
Iteration 45 	 0.5624995121567982 					 0.5624995121567982 
Iteration 46 	 0.5624995121567982 					 0.5624995121567982 
Iteration 47 	 0.5624995121567982 					 0.5624995121567982 
Iteration 48 	 0.5624995121567982 					 0.5624995121567982 
Iteration 49 	 0.5624995121567982 					 0.5624995121567982 


 ----------------------------------------------------------------------------------------
Run Number - 20
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.34808706072595674 					 0.34808706072595674 
Iteration 1 	 0.4287987096155834 					 0.4287987096155834 
Iteration 2 	 0.43029095547388985 					 0.43029095547388985 
Iteration 3 	 0.496070316152103 					 0.496070316152103 
Iteration 4 	 0.5237654425978991 					 0.5237654425978991 
Iteration 5 	 0.5156383950541026 					 0.5237654425978991 
Iteration 6 	 0.525212479456081 					 0.525212479456081 
Iteration 7 	 0.513498063333778 					 0.525212479456081 
Iteration 8 	 0.5293646902244374 					 0.5293646902244374 
Iteration 9 	 0.5293646902244374 					 0.5293646902244374 
Iteration 10 	 0.5435479935983084 					 0.5435479935983084 
Iteration 11 	 0.5254893050166622 					 0.5435479935983084 
Iteration 12 	 0.5146208263888868 					 0.5435479935983084 
Iteration 13 	 0.5358981058576552 					 0.5435479935983084 
Iteration 14 	 0.5358981058576552 					 0.5435479935983084 
Iteration 15 	 0.5183366434432407 					 0.5435479935983084 
Iteration 16 	 0.5183366434432407 					 0.5435479935983084 
Iteration 17 	 0.5183366434432407 					 0.5435479935983084 
Iteration 18 	 0.5146208263888868 					 0.5435479935983084 
Iteration 19 	 0.5146208263888868 					 0.5435479935983084 
Iteration 20 	 0.5146208263888868 					 0.5435479935983084 
Iteration 21 	 0.5146208263888868 					 0.5435479935983084 
Iteration 22 	 0.5146208263888868 					 0.5435479935983084 
Iteration 23 	 0.5146208263888868 					 0.5435479935983084 
Iteration 24 	 0.5146208263888868 					 0.5435479935983084 
Iteration 25 	 0.5146208263888868 					 0.5435479935983084 
Iteration 26 	 0.5146208263888868 					 0.5435479935983084 
Iteration 27 	 0.5146208263888868 					 0.5435479935983084 
Iteration 28 	 0.5146208263888868 					 0.5435479935983084 
Iteration 29 	 0.5146208263888868 					 0.5435479935983084 
Iteration 30 	 0.5146208263888868 					 0.5435479935983084 
Iteration 31 	 0.5146208263888868 					 0.5435479935983084 
Iteration 32 	 0.5146208263888868 					 0.5435479935983084 
Iteration 33 	 0.5146208263888868 					 0.5435479935983084 
Iteration 34 	 0.5146208263888868 					 0.5435479935983084 
Iteration 35 	 0.5146208263888868 					 0.5435479935983084 
Iteration 36 	 0.5146208263888868 					 0.5435479935983084 
Iteration 37 	 0.5146208263888868 					 0.5435479935983084 
Iteration 38 	 0.5146208263888868 					 0.5435479935983084 
Iteration 39 	 0.5146208263888868 					 0.5435479935983084 
Iteration 40 	 0.5146208263888868 					 0.5435479935983084 
Iteration 41 	 0.5146208263888868 					 0.5435479935983084 
Iteration 42 	 0.5146208263888868 					 0.5435479935983084 
Iteration 43 	 0.5146208263888868 					 0.5435479935983084 
Iteration 44 	 0.5146208263888868 					 0.5435479935983084 
Iteration 45 	 0.5146208263888868 					 0.5435479935983084 
Iteration 46 	 0.5146208263888868 					 0.5435479935983084 
Iteration 47 	 0.5146208263888868 					 0.5435479935983084 
Iteration 48 	 0.5146208263888868 					 0.5435479935983084 
Iteration 49 	 0.5146208263888868 					 0.5435479935983084


solutions_linear['best_solution']

{'run_id': 6,
 'best_score': 0.5684046529252416,
 'num_features': 275,
 'selected_features': ['ALogP',
  'AMR',
  'apol',
  'nHeavyAtom',
  'nH',
  'nN',
  'nS',
  'nX',
  'ATS0m',
  'ATS1m',
  'ATS2m',
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  'ATS3v',
  'ATS5v',
  'ATS7v',
  'ATS8v',
  'ATS3e',
  'ATS4e',
  'ATS5e',
  'ATS6e',
  'ATS7e',
  'ATS0p',
  'ATS3p',
  'ATS4p',
  'ATS6p',
  'ATS8p',
  'ATS1i',
  'ATS2i',
  'ATS3i',
  'ATS5i',
  'ATS6i',
  'ATS8i',
  'ATS2s',
  'ATS5s',
  'ATS6s',
  'ATS7s',
  'AATS1m',
  'AATS2m',
  'AATS5m',
  'AATS6m',
  'AATS7m',
  'AATS0v',
  'AATS1v',
  'AATS2v',
  'AATS3v',
  'AATS4v',
  'AATS7v',
  'AATS8v',
  'AATS2i',
  'AATS6i',
  'AATS7i',
  'AATS8i',
  'AATS4s',
  'ATSC1m',
  'ATSC2m',
  'ATSC4m',
  'ATSC5m',
  'ATSC6m',
  'ATSC8m',
  'ATSC0v',
  'ATSC2v',
  'ATSC4v',
  'ATSC5v',
  'ATSC6v',
  'ATSC7v',
  'ATSC8v',
  'ATSC6e',
  'ATSC0p',
  'ATSC1p',
  'ATSC3p',
  'ATSC4p',
  'ATSC5p',
  'ATSC2i',
  'ATSC3i',
  'ATSC4i',
  'ATSC5i',
  'ATSC6i',
  'ATSC7i',
  'ATSC8i',
  'AATSC0m',
  'AATSC6m',
  'AATSC8m',
  'AATSC6v',
  'AATSC7v',
  'SpDiam_DzZ',
  'SpAD_DzZ',
  'EE_DzZ',
  'VR1_DzZ',
  'VR3_DzZ',
  'SpAbs_Dzm',
  'SpDiam_Dzm',
  'SpMAD_Dzm',
  'SM1_Dzm',
  'VR2_Dzm',
  'SpAbs_Dzv',
  'SpDiam_Dzv',
  'SpAD_Dzv',
  'SpMAD_Dzv',
  'EE_Dzv',
  'VE3_Dzv',
  'VR3_Dzv',
  'SpAbs_Dze',
  'SpAD_Dze',
  'SpMAD_Dze',
  'EE_Dze',
  'VR3_Dze',
  'SpAbs_Dzp',
  'SpDiam_Dzp',
  'SpAD_Dzp',
  'SpMAD_Dzp',
  'EE_Dzp',
  'VE3_Dzp',
  'SpAbs_Dzi',
  'SpDiam_Dzi',
  'SpAD_Dzi',
  'VE3_Dzi',
  'VR1_Dzi',
  'VR3_Dzi',
  'SpAbs_Dzs',
  'SpAD_Dzs',
  'EE_Dzs',
  'SM1_Dzs',
  'VE3_Dzs',
  'VR1_Dzs',
  'VR2_Dzs',
  'VR3_Dzs',
  'BCUTp-1h',
  'nBondsS2',
  'C2SP2',
  'C3SP2',
  'C1SP3',
  'C2SP3',
  'SC-3',
  'SPC-4',
  'SPC-5',
  'VPC-4',
  'SP-0',
  'SP-1',
  'SP-2',
  'SP-5',
  'VP-0',
  'VP-6',
  'Sv',
  'Sse',
  'Spe',
  'Sare',
  'Sp',
  'Si',
  'CrippenMR',
  'SpMax_Dt',
  'SpDiam_Dt',
  'SpAD_Dt',
  'VR3_Dt',
  'nHBd',
  'nwHBa',
  'nHBint3',
  'nHBint4',
  'nHBint10',
  'nHsOH',
  'nHdsCH',
  'nHaaCH',
  'nHother',
  'nsCH3',
  'nssCH2',
  'naaCH',
  'nsssCH',
  'naaN',
  'nsssN',
  'nsOH',
  'SHBint2',
  'SHBint3',
  'SHBint6',
  'SHBint7',
  'SHBint9',
  'SHaaCH',
  'SHCsats',
  'SHCsatu',
  'SHother',
  'SssCH2',
  'SsssCH',
  'SdssC',
  'SaasC',
  'SaaaC',
  'SssssC',
  'SsNH2',
  'SssNH',
  'SdsN',
  'SsssN',
  'SsOH',
  'SssO',
  'SsF',
  'SddssS',
  'minHBint6',
  'minHBint7',
  'minsNH2',
  'minssNH',
  'mintN',
  'mindO',
  'maxHBint5',
  'maxHBint7',
  'maxdsCH',
  'maxsNH2',
  'maxdsN',
  'maxaaN',
  'maxdO',
  'maxssO',
  'maxsOm',
  'maxsF',
  'gmax',
  'MAXDP',
  'MAXDN2',
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  'ETA_Beta_s',
  'ETA_dBeta',
  'ETA_Beta_ns_d',
  'ETA_Eta_R',
  'ETA_Eta_F',
  'ETA_Eta_R_L',
  'nHBAcc2',
  'nHBDon',
  'nHBDon_Lipinski',
  'TIC0',
  'TIC1',
  'TIC4',
  'TIC5',
  'MIC0',
  'MIC5',
  'ZMIC1',
  'ZMIC5',
  'Kier2',
  'nAtomLC',
  'MDEC-12',
  'MDEC-13',
  'MDEC-23',
  'MDEC-24',
  'MDEC-33',
  'MDEO-11',
  'MDEN-22',
  'MLFER_BO',
  'MLFER_S',
  'MLFER_L',
  'MPC3',
  'MPC5',
  'MPC6',
  'MPC7',
  'MPC8',
  'TPC',
  'piPC9',
  'piPC10',
  'nRing',
  'n6Ring',
  'nT6Ring',
  'nTG12Ring',
  'n6HeteroRing',
  'nFG12HeteroRing',
  'nT6HeteroRing',
  'nTG12HeteroRing',
  'nRotB',
  'topoDiameter',
  'GGI3',
  'GGI4',
  'SpAD_D',
  'VE3_D',
  'VR1_D',
  'TWC',
  'SRW9',
  'AMW',
  'WTPT-3',
  'WTPT-4',
  'WTPT-5',
  'WPATH',
  'XLogP'],
 'plot': Figure({
     'data': [{'mode': 'markers',
               'name': 'objective_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.40338760962919584, 0.3863827033200282, 0.3773252804644625,
                           0.4852616607192198, 0.44764442540594507, 0.44764442540594507,
                           0.49240330515892017, 0.49240330515892017, 0.49240330515892017,
                           0.4890293424451058, 0.5083925207889659, 0.50072076897502,
                           0.5135307773433996, 0.5486159011373252, 0.5677472852913446,
                           0.5677472852913446, 0.5684046529252416, 0.5684046529252416,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446, 0.5677472852913446,
                           0.5677472852913446, 0.5677472852913446], dtype=object)},
              {'mode': 'lines+markers',
               'name': 'best_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.40338760962919584, 0.40338760962919584, 0.40338760962919584,
                           0.4852616607192198, 0.4852616607192198, 0.4852616607192198,
                           0.49240330515892017, 0.49240330515892017, 0.49240330515892017,
                           0.49240330515892017, 0.5083925207889659, 0.5083925207889659,
                           0.5135307773433996, 0.5486159011373252, 0.5677472852913446,
                           0.5677472852913446, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416, 0.5684046529252416,
                           0.5684046529252416, 0.5684046529252416], dtype=object)}],
     'layout': {'template': '...',
                'title': {'text': 'Optimization History Plot'},
                'xaxis': {'title': {'text': 'Iteration'}},
                'yaxis': {'title': {'text': 'objective_score'}}}
 })}


solutions_linear['best_solution']['plot']


# Define machine learning model
svr_rbf_model = SVR(kernel='rbf')
# Multiple run GA with those machine learning model
solutions_rbf = multiple_run_fs(20, svr_rbf_model, X_train, y_train, X_valid, y_valid)


 ----------------------------------------------------------------------------------------
Run Number - 1
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.638003835608042 					 0.638003835608042 
Iteration 1 	 0.6355371319727348 					 0.638003835608042 
Iteration 2 	 0.6356374867804335 					 0.638003835608042 
Iteration 3 	 0.640302421554967 					 0.640302421554967 
Iteration 4 	 0.6403711368232415 					 0.6403711368232415 
Iteration 5 	 0.6439680352965844 					 0.6439680352965844 
Iteration 6 	 0.6438268768090838 					 0.6439680352965844 
Iteration 7 	 0.6436825744581509 					 0.6439680352965844 
Iteration 8 	 0.6452841380775219 					 0.6452841380775219 
Iteration 9 	 0.6452841380775219 					 0.6452841380775219 
Iteration 10 	 0.6452841380775219 					 0.6452841380775219 
Iteration 11 	 0.6453156904552024 					 0.6453156904552024 
Iteration 12 	 0.6453156904552024 					 0.6453156904552024 
Iteration 13 	 0.6453156904552024 					 0.6453156904552024 
Iteration 14 	 0.6461215127966908 					 0.6461215127966908 
Iteration 15 	 0.6453156904552024 					 0.6461215127966908 
Iteration 16 	 0.6453156904552024 					 0.6461215127966908 
Iteration 17 	 0.6457204038094486 					 0.6461215127966908 
Iteration 18 	 0.6452841380775219 					 0.6461215127966908 
Iteration 19 	 0.6452841380775219 					 0.6461215127966908 
Iteration 20 	 0.6452841380775219 					 0.6461215127966908 
Iteration 21 	 0.6452841380775219 					 0.6461215127966908 
Iteration 22 	 0.6452841380775219 					 0.6461215127966908 
Iteration 23 	 0.6452841380775219 					 0.6461215127966908 
Iteration 24 	 0.6452841380775219 					 0.6461215127966908 
Iteration 25 	 0.6452841380775219 					 0.6461215127966908 
Iteration 26 	 0.6452841380775219 					 0.6461215127966908 
Iteration 27 	 0.6452841380775219 					 0.6461215127966908 
Iteration 28 	 0.6452841380775219 					 0.6461215127966908 
Iteration 29 	 0.6452841380775219 					 0.6461215127966908 
Iteration 30 	 0.6452841380775219 					 0.6461215127966908 
Iteration 31 	 0.6452841380775219 					 0.6461215127966908 
Iteration 32 	 0.6452841380775219 					 0.6461215127966908 
Iteration 33 	 0.6452841380775219 					 0.6461215127966908 
Iteration 34 	 0.6452841380775219 					 0.6461215127966908 
Iteration 35 	 0.6452841380775219 					 0.6461215127966908 
Iteration 36 	 0.6452841380775219 					 0.6461215127966908 
Iteration 37 	 0.6452841380775219 					 0.6461215127966908 
Iteration 38 	 0.6452841380775219 					 0.6461215127966908 
Iteration 39 	 0.6452841380775219 					 0.6461215127966908 
Iteration 40 	 0.6452841380775219 					 0.6461215127966908 
Iteration 41 	 0.6452841380775219 					 0.6461215127966908 
Iteration 42 	 0.6452841380775219 					 0.6461215127966908 
Iteration 43 	 0.6452841380775219 					 0.6461215127966908 
Iteration 44 	 0.6452841380775219 					 0.6461215127966908 
Iteration 45 	 0.6452841380775219 					 0.6461215127966908 
Iteration 46 	 0.6452841380775219 					 0.6461215127966908 
Iteration 47 	 0.6452841380775219 					 0.6461215127966908 
Iteration 48 	 0.6452841380775219 					 0.6461215127966908 
Iteration 49 	 0.6452841380775219 					 0.6461215127966908 


 ----------------------------------------------------------------------------------------
Run Number - 2
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.651599682212262 					 0.651599682212262 
Iteration 1 	 0.6506529705844517 					 0.651599682212262 
Iteration 2 	 0.6516846092769547 					 0.6516846092769547 
Iteration 3 	 0.6512115608721519 					 0.6516846092769547 
Iteration 4 	 0.6511431890289382 					 0.6516846092769547 
Iteration 5 	 0.651824966479658 					 0.651824966479658 
Iteration 6 	 0.6527249944277715 					 0.6527249944277715 
Iteration 7 	 0.654207185446191 					 0.654207185446191 
Iteration 8 	 0.654207185446191 					 0.654207185446191 
Iteration 9 	 0.6537014117363981 					 0.654207185446191 
Iteration 10 	 0.6541463716563397 					 0.654207185446191 
Iteration 11 	 0.654207185446191 					 0.654207185446191 
Iteration 12 	 0.654207185446191 					 0.654207185446191 
Iteration 13 	 0.6562186016462221 					 0.6562186016462221 
Iteration 14 	 0.6562186016462221 					 0.6562186016462221 
Iteration 15 	 0.6562186016462221 					 0.6562186016462221 
Iteration 16 	 0.6562186016462221 					 0.6562186016462221 
Iteration 17 	 0.6562186016462221 					 0.6562186016462221 
Iteration 18 	 0.6562186016462221 					 0.6562186016462221 
Iteration 19 	 0.6562186016462221 					 0.6562186016462221 
Iteration 20 	 0.6562186016462221 					 0.6562186016462221 
Iteration 21 	 0.6562186016462221 					 0.6562186016462221 
Iteration 22 	 0.6562186016462221 					 0.6562186016462221 
Iteration 23 	 0.6562186016462221 					 0.6562186016462221 
Iteration 24 	 0.6562186016462221 					 0.6562186016462221 
Iteration 25 	 0.6562186016462221 					 0.6562186016462221 
Iteration 26 	 0.6562186016462221 					 0.6562186016462221 
Iteration 27 	 0.6562186016462221 					 0.6562186016462221 
Iteration 28 	 0.6562186016462221 					 0.6562186016462221 
Iteration 29 	 0.6562186016462221 					 0.6562186016462221 
Iteration 30 	 0.6562186016462221 					 0.6562186016462221 
Iteration 31 	 0.6562186016462221 					 0.6562186016462221 
Iteration 32 	 0.6562186016462221 					 0.6562186016462221 
Iteration 33 	 0.6562186016462221 					 0.6562186016462221 
Iteration 34 	 0.6562186016462221 					 0.6562186016462221 
Iteration 35 	 0.6562186016462221 					 0.6562186016462221 
Iteration 36 	 0.6562186016462221 					 0.6562186016462221 
Iteration 37 	 0.6562186016462221 					 0.6562186016462221 
Iteration 38 	 0.6562186016462221 					 0.6562186016462221 
Iteration 39 	 0.6562186016462221 					 0.6562186016462221 
Iteration 40 	 0.6562186016462221 					 0.6562186016462221 
Iteration 41 	 0.6562186016462221 					 0.6562186016462221 
Iteration 42 	 0.6562186016462221 					 0.6562186016462221 
Iteration 43 	 0.6562186016462221 					 0.6562186016462221 
Iteration 44 	 0.6562186016462221 					 0.6562186016462221 
Iteration 45 	 0.6562186016462221 					 0.6562186016462221 
Iteration 46 	 0.6562186016462221 					 0.6562186016462221 
Iteration 47 	 0.6562186016462221 					 0.6562186016462221 
Iteration 48 	 0.6562186016462221 					 0.6562186016462221 
Iteration 49 	 0.6562186016462221 					 0.6562186016462221 


 ----------------------------------------------------------------------------------------
Run Number - 3
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6477606698251651 					 0.6477606698251651 
Iteration 1 	 0.6506139445704683 					 0.6506139445704683 
Iteration 2 	 0.6492616499819752 					 0.6506139445704683 
Iteration 3 	 0.6554295229412225 					 0.6554295229412225 
Iteration 4 	 0.6548107398650584 					 0.6554295229412225 
Iteration 5 	 0.6568151889492566 					 0.6568151889492566 
Iteration 6 	 0.6568151889492566 					 0.6568151889492566 
Iteration 7 	 0.6589269508361247 					 0.6589269508361247 
Iteration 8 	 0.6592280499167187 					 0.6592280499167187 
Iteration 9 	 0.659892793432256 					 0.659892793432256 
Iteration 10 	 0.661201455020388 					 0.661201455020388 
Iteration 11 	 0.6611167439765863 					 0.661201455020388 
Iteration 12 	 0.6619392617621461 					 0.6619392617621461 
Iteration 13 	 0.6640771994226359 					 0.6640771994226359 
Iteration 14 	 0.6640771994226359 					 0.6640771994226359 
Iteration 15 	 0.6654984029635836 					 0.6654984029635836 
Iteration 16 	 0.6654984029635836 					 0.6654984029635836 
Iteration 17 	 0.6654984029635836 					 0.6654984029635836 
Iteration 18 	 0.6654984029635836 					 0.6654984029635836 
Iteration 19 	 0.6654984029635836 					 0.6654984029635836 
Iteration 20 	 0.6654984029635836 					 0.6654984029635836 
Iteration 21 	 0.6654984029635836 					 0.6654984029635836 
Iteration 22 	 0.6654984029635836 					 0.6654984029635836 
Iteration 23 	 0.6654984029635836 					 0.6654984029635836 
Iteration 24 	 0.6654984029635836 					 0.6654984029635836 
Iteration 25 	 0.6654984029635836 					 0.6654984029635836 
Iteration 26 	 0.6654984029635836 					 0.6654984029635836 
Iteration 27 	 0.6654984029635836 					 0.6654984029635836 
Iteration 28 	 0.6654984029635836 					 0.6654984029635836 
Iteration 29 	 0.6654984029635836 					 0.6654984029635836 
Iteration 30 	 0.6654984029635836 					 0.6654984029635836 
Iteration 31 	 0.6654984029635836 					 0.6654984029635836 
Iteration 32 	 0.6654984029635836 					 0.6654984029635836 
Iteration 33 	 0.6654984029635836 					 0.6654984029635836 
Iteration 34 	 0.6654984029635836 					 0.6654984029635836 
Iteration 35 	 0.6654984029635836 					 0.6654984029635836 
Iteration 36 	 0.6654984029635836 					 0.6654984029635836 
Iteration 37 	 0.6654984029635836 					 0.6654984029635836 
Iteration 38 	 0.6654984029635836 					 0.6654984029635836 
Iteration 39 	 0.6654984029635836 					 0.6654984029635836 
Iteration 40 	 0.6654984029635836 					 0.6654984029635836 
Iteration 41 	 0.6654984029635836 					 0.6654984029635836 
Iteration 42 	 0.6654984029635836 					 0.6654984029635836 
Iteration 43 	 0.6654984029635836 					 0.6654984029635836 
Iteration 44 	 0.6654984029635836 					 0.6654984029635836 
Iteration 45 	 0.6654984029635836 					 0.6654984029635836 
Iteration 46 	 0.6654984029635836 					 0.6654984029635836 
Iteration 47 	 0.6654984029635836 					 0.6654984029635836 
Iteration 48 	 0.6654984029635836 					 0.6654984029635836 
Iteration 49 	 0.6654984029635836 					 0.6654984029635836 


 ----------------------------------------------------------------------------------------
Run Number - 4
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.650564026634284 					 0.650564026634284 
Iteration 1 	 0.6454541364075498 					 0.650564026634284 
Iteration 2 	 0.6503816122805114 					 0.650564026634284 
Iteration 3 	 0.6498440881849827 					 0.650564026634284 
Iteration 4 	 0.6498440881849827 					 0.650564026634284 
Iteration 5 	 0.6498440881849827 					 0.650564026634284 
Iteration 6 	 0.6503273610459192 					 0.650564026634284 
Iteration 7 	 0.6518582977227207 					 0.6518582977227207 
Iteration 8 	 0.6520614330223496 					 0.6520614330223496 
Iteration 9 	 0.6518582977227207 					 0.6520614330223496 
Iteration 10 	 0.6523152341568038 					 0.6523152341568038 
Iteration 11 	 0.6523152341568038 					 0.6523152341568038 
Iteration 12 	 0.6523152341568038 					 0.6523152341568038 
Iteration 13 	 0.652461742276265 					 0.652461742276265 
Iteration 14 	 0.6523152341568038 					 0.652461742276265 
Iteration 15 	 0.6523152341568038 					 0.652461742276265 
Iteration 16 	 0.6523152341568038 					 0.652461742276265 
Iteration 17 	 0.6523152341568038 					 0.652461742276265 
Iteration 18 	 0.6523152341568038 					 0.652461742276265 
Iteration 19 	 0.6523152341568038 					 0.652461742276265 
Iteration 20 	 0.6523152341568038 					 0.652461742276265 
Iteration 21 	 0.6523152341568038 					 0.652461742276265 
Iteration 22 	 0.6523152341568038 					 0.652461742276265 
Iteration 23 	 0.6523152341568038 					 0.652461742276265 
Iteration 24 	 0.6523152341568038 					 0.652461742276265 
Iteration 25 	 0.6523152341568038 					 0.652461742276265 
Iteration 26 	 0.6523152341568038 					 0.652461742276265 
Iteration 27 	 0.6523152341568038 					 0.652461742276265 
Iteration 28 	 0.6523152341568038 					 0.652461742276265 
Iteration 29 	 0.6523152341568038 					 0.652461742276265 
Iteration 30 	 0.6523152341568038 					 0.652461742276265 
Iteration 31 	 0.6523152341568038 					 0.652461742276265 
Iteration 32 	 0.6523152341568038 					 0.652461742276265 
Iteration 33 	 0.6523152341568038 					 0.652461742276265 
Iteration 34 	 0.6523152341568038 					 0.652461742276265 
Iteration 35 	 0.6523152341568038 					 0.652461742276265 
Iteration 36 	 0.6523152341568038 					 0.652461742276265 
Iteration 37 	 0.6523152341568038 					 0.652461742276265 
Iteration 38 	 0.6523152341568038 					 0.652461742276265 
Iteration 39 	 0.6523152341568038 					 0.652461742276265 
Iteration 40 	 0.6523152341568038 					 0.652461742276265 
Iteration 41 	 0.6523152341568038 					 0.652461742276265 
Iteration 42 	 0.6523152341568038 					 0.652461742276265 
Iteration 43 	 0.6523152341568038 					 0.652461742276265 
Iteration 44 	 0.6523152341568038 					 0.652461742276265 
Iteration 45 	 0.6523152341568038 					 0.652461742276265 
Iteration 46 	 0.6523152341568038 					 0.652461742276265 
Iteration 47 	 0.6523152341568038 					 0.652461742276265 
Iteration 48 	 0.6523152341568038 					 0.652461742276265 
Iteration 49 	 0.6523152341568038 					 0.652461742276265 


 ----------------------------------------------------------------------------------------
Run Number - 5
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.643555301300432 					 0.643555301300432 
Iteration 1 	 0.6536346419121941 					 0.6536346419121941 
Iteration 2 	 0.6530516096371444 					 0.6536346419121941 
Iteration 3 	 0.6453062066059517 					 0.6536346419121941 
Iteration 4 	 0.6528353203644158 					 0.6536346419121941 
Iteration 5 	 0.654057605091106 					 0.654057605091106 
Iteration 6 	 0.6559113404904071 					 0.6559113404904071 
Iteration 7 	 0.6565298567938296 					 0.6565298567938296 
Iteration 8 	 0.6563796769825152 					 0.6565298567938296 
Iteration 9 	 0.6563796769825152 					 0.6565298567938296 
Iteration 10 	 0.656578054500534 					 0.656578054500534 
Iteration 11 	 0.656578054500534 					 0.656578054500534 
Iteration 12 	 0.656578054500534 					 0.656578054500534 
Iteration 13 	 0.656578054500534 					 0.656578054500534 
Iteration 14 	 0.656578054500534 					 0.656578054500534 
Iteration 15 	 0.656578054500534 					 0.656578054500534 
Iteration 16 	 0.656578054500534 					 0.656578054500534 
Iteration 17 	 0.656578054500534 					 0.656578054500534 
Iteration 18 	 0.656578054500534 					 0.656578054500534 
Iteration 19 	 0.656578054500534 					 0.656578054500534 
Iteration 20 	 0.656578054500534 					 0.656578054500534 
Iteration 21 	 0.656578054500534 					 0.656578054500534 
Iteration 22 	 0.656578054500534 					 0.656578054500534 
Iteration 23 	 0.656578054500534 					 0.656578054500534 
Iteration 24 	 0.656578054500534 					 0.656578054500534 
Iteration 25 	 0.656578054500534 					 0.656578054500534 
Iteration 26 	 0.656578054500534 					 0.656578054500534 
Iteration 27 	 0.656578054500534 					 0.656578054500534 
Iteration 28 	 0.656578054500534 					 0.656578054500534 
Iteration 29 	 0.656578054500534 					 0.656578054500534 
Iteration 30 	 0.656578054500534 					 0.656578054500534 
Iteration 31 	 0.656578054500534 					 0.656578054500534 
Iteration 32 	 0.656578054500534 					 0.656578054500534 
Iteration 33 	 0.656578054500534 					 0.656578054500534 
Iteration 34 	 0.656578054500534 					 0.656578054500534 
Iteration 35 	 0.656578054500534 					 0.656578054500534 
Iteration 36 	 0.656578054500534 					 0.656578054500534 
Iteration 37 	 0.656578054500534 					 0.656578054500534 
Iteration 38 	 0.656578054500534 					 0.656578054500534 
Iteration 39 	 0.656578054500534 					 0.656578054500534 
Iteration 40 	 0.656578054500534 					 0.656578054500534 
Iteration 41 	 0.656578054500534 					 0.656578054500534 
Iteration 42 	 0.656578054500534 					 0.656578054500534 
Iteration 43 	 0.656578054500534 					 0.656578054500534 
Iteration 44 	 0.656578054500534 					 0.656578054500534 
Iteration 45 	 0.656578054500534 					 0.656578054500534 
Iteration 46 	 0.656578054500534 					 0.656578054500534 
Iteration 47 	 0.656578054500534 					 0.656578054500534 
Iteration 48 	 0.656578054500534 					 0.656578054500534 
Iteration 49 	 0.656578054500534 					 0.656578054500534 


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Run Number - 6
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6409423281948579 					 0.6409423281948579 
Iteration 1 	 0.6358127331830624 					 0.6409423281948579 
Iteration 2 	 0.6380068621888616 					 0.6409423281948579 
Iteration 3 	 0.6380068621888616 					 0.6409423281948579 
Iteration 4 	 0.6380068621888616 					 0.6409423281948579 
Iteration 5 	 0.6380068621888616 					 0.6409423281948579 
Iteration 6 	 0.6385033338190719 					 0.6409423281948579 
Iteration 7 	 0.6380068621888616 					 0.6409423281948579 
Iteration 8 	 0.6380068621888616 					 0.6409423281948579 
Iteration 9 	 0.6380068621888616 					 0.6409423281948579 
Iteration 10 	 0.6380068621888616 					 0.6409423281948579 
Iteration 11 	 0.6380068621888616 					 0.6409423281948579 
Iteration 12 	 0.6380068621888616 					 0.6409423281948579 
Iteration 13 	 0.6380068621888616 					 0.6409423281948579 
Iteration 14 	 0.6380068621888616 					 0.6409423281948579 
Iteration 15 	 0.6380068621888616 					 0.6409423281948579 
Iteration 16 	 0.6380068621888616 					 0.6409423281948579 
Iteration 17 	 0.6380068621888616 					 0.6409423281948579 
Iteration 18 	 0.6380068621888616 					 0.6409423281948579 
Iteration 19 	 0.6380068621888616 					 0.6409423281948579 
Iteration 20 	 0.6380068621888616 					 0.6409423281948579 
Iteration 21 	 0.6380068621888616 					 0.6409423281948579 
Iteration 22 	 0.6380068621888616 					 0.6409423281948579 
Iteration 23 	 0.6380068621888616 					 0.6409423281948579 
Iteration 24 	 0.6380068621888616 					 0.6409423281948579 
Iteration 25 	 0.6380068621888616 					 0.6409423281948579 
Iteration 26 	 0.6380068621888616 					 0.6409423281948579 
Iteration 27 	 0.6380068621888616 					 0.6409423281948579 
Iteration 28 	 0.6380068621888616 					 0.6409423281948579 
Iteration 29 	 0.6380068621888616 					 0.6409423281948579 
Iteration 30 	 0.6380068621888616 					 0.6409423281948579 
Iteration 31 	 0.6380068621888616 					 0.6409423281948579 
Iteration 32 	 0.6380068621888616 					 0.6409423281948579 
Iteration 33 	 0.6380068621888616 					 0.6409423281948579 
Iteration 34 	 0.6380068621888616 					 0.6409423281948579 
Iteration 35 	 0.6380068621888616 					 0.6409423281948579 
Iteration 36 	 0.6380068621888616 					 0.6409423281948579 
Iteration 37 	 0.6380068621888616 					 0.6409423281948579 
Iteration 38 	 0.6380068621888616 					 0.6409423281948579 
Iteration 39 	 0.6380068621888616 					 0.6409423281948579 
Iteration 40 	 0.6380068621888616 					 0.6409423281948579 
Iteration 41 	 0.6380068621888616 					 0.6409423281948579 
Iteration 42 	 0.6380068621888616 					 0.6409423281948579 
Iteration 43 	 0.6380068621888616 					 0.6409423281948579 
Iteration 44 	 0.6380068621888616 					 0.6409423281948579 
Iteration 45 	 0.6380068621888616 					 0.6409423281948579 
Iteration 46 	 0.6380068621888616 					 0.6409423281948579 
Iteration 47 	 0.6380068621888616 					 0.6409423281948579 
Iteration 48 	 0.6380068621888616 					 0.6409423281948579 
Iteration 49 	 0.6380068621888616 					 0.6409423281948579 


 ----------------------------------------------------------------------------------------
Run Number - 7
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.643815044410458 					 0.643815044410458 
Iteration 1 	 0.6430254390858949 					 0.643815044410458 
Iteration 2 	 0.6452952307507183 					 0.6452952307507183 
Iteration 3 	 0.6450065155491983 					 0.6452952307507183 
Iteration 4 	 0.6462331162436631 					 0.6462331162436631 
Iteration 5 	 0.6472801882431002 					 0.6472801882431002 
Iteration 6 	 0.6445793718348473 					 0.6472801882431002 
Iteration 7 	 0.6445793718348473 					 0.6472801882431002 
Iteration 8 	 0.646977185931836 					 0.6472801882431002 
Iteration 9 	 0.646977185931836 					 0.6472801882431002 
Iteration 10 	 0.6471725894743108 					 0.6472801882431002 
Iteration 11 	 0.6471725894743108 					 0.6472801882431002 
Iteration 12 	 0.6475978344275591 					 0.6475978344275591 
Iteration 13 	 0.6479052701889751 					 0.6479052701889751 
Iteration 14 	 0.6479052701889751 					 0.6479052701889751 
Iteration 15 	 0.6483044197055917 					 0.6483044197055917 
Iteration 16 	 0.6496194664694677 					 0.6496194664694677 
Iteration 17 	 0.6523426887256887 					 0.6523426887256887 
Iteration 18 	 0.6520252146304594 					 0.6523426887256887 
Iteration 19 	 0.6520252146304594 					 0.6523426887256887 
Iteration 20 	 0.652391911889136 					 0.652391911889136 
Iteration 21 	 0.6520252146304594 					 0.652391911889136 
Iteration 22 	 0.6520252146304594 					 0.652391911889136 
Iteration 23 	 0.6520252146304594 					 0.652391911889136 
Iteration 24 	 0.6520252146304594 					 0.652391911889136 
Iteration 25 	 0.6521685501692259 					 0.652391911889136 
Iteration 26 	 0.6521685501692259 					 0.652391911889136 
Iteration 27 	 0.6521685501692259 					 0.652391911889136 
Iteration 28 	 0.6521685501692259 					 0.652391911889136 
Iteration 29 	 0.6520252146304594 					 0.652391911889136 
Iteration 30 	 0.6520252146304594 					 0.652391911889136 
Iteration 31 	 0.6520252146304594 					 0.652391911889136 
Iteration 32 	 0.6520252146304594 					 0.652391911889136 
Iteration 33 	 0.6520252146304594 					 0.652391911889136 
Iteration 34 	 0.6520252146304594 					 0.652391911889136 
Iteration 35 	 0.6520252146304594 					 0.652391911889136 
Iteration 36 	 0.6520252146304594 					 0.652391911889136 
Iteration 37 	 0.6520252146304594 					 0.652391911889136 
Iteration 38 	 0.6520252146304594 					 0.652391911889136 
Iteration 39 	 0.6520252146304594 					 0.652391911889136 
Iteration 40 	 0.6520252146304594 					 0.652391911889136 
Iteration 41 	 0.6520252146304594 					 0.652391911889136 
Iteration 42 	 0.6520252146304594 					 0.652391911889136 
Iteration 43 	 0.6520252146304594 					 0.652391911889136 
Iteration 44 	 0.6520252146304594 					 0.652391911889136 
Iteration 45 	 0.6520252146304594 					 0.652391911889136 
Iteration 46 	 0.6520252146304594 					 0.652391911889136 
Iteration 47 	 0.6520252146304594 					 0.652391911889136 
Iteration 48 	 0.6520252146304594 					 0.652391911889136 
Iteration 49 	 0.6520252146304594 					 0.652391911889136 


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Run Number - 8
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6409312126656229 					 0.6409312126656229 
Iteration 1 	 0.644821607360237 					 0.644821607360237 
Iteration 2 	 0.6443170444761877 					 0.644821607360237 
Iteration 3 	 0.651697491000143 					 0.651697491000143 
Iteration 4 	 0.6510166542234975 					 0.651697491000143 
Iteration 5 	 0.6531944389062739 					 0.6531944389062739 
Iteration 6 	 0.6532338386591685 					 0.6532338386591685 
Iteration 7 	 0.6556851417861808 					 0.6556851417861808 
Iteration 8 	 0.6551113489705955 					 0.6556851417861808 
Iteration 9 	 0.655534111894914 					 0.6556851417861808 
Iteration 10 	 0.6551113489705955 					 0.6556851417861808 
Iteration 11 	 0.6551113489705955 					 0.6556851417861808 
Iteration 12 	 0.6524316510413181 					 0.6556851417861808 
Iteration 13 	 0.6524316510413181 					 0.6556851417861808 
Iteration 14 	 0.6524316510413181 					 0.6556851417861808 
Iteration 15 	 0.6524316510413181 					 0.6556851417861808 
Iteration 16 	 0.6524316510413181 					 0.6556851417861808 
Iteration 17 	 0.6532180746328442 					 0.6556851417861808 
Iteration 18 	 0.6532180746328442 					 0.6556851417861808 
Iteration 19 	 0.6532180746328442 					 0.6556851417861808 
Iteration 20 	 0.6532180746328442 					 0.6556851417861808 
Iteration 21 	 0.6532180746328442 					 0.6556851417861808 
Iteration 22 	 0.6532180746328442 					 0.6556851417861808 
Iteration 23 	 0.6532180746328442 					 0.6556851417861808 
Iteration 24 	 0.6532180746328442 					 0.6556851417861808 
Iteration 25 	 0.6532180746328442 					 0.6556851417861808 
Iteration 26 	 0.6532180746328442 					 0.6556851417861808 
Iteration 27 	 0.6532180746328442 					 0.6556851417861808 
Iteration 28 	 0.6532180746328442 					 0.6556851417861808 
Iteration 29 	 0.6532180746328442 					 0.6556851417861808 
Iteration 30 	 0.6532180746328442 					 0.6556851417861808 
Iteration 31 	 0.6532180746328442 					 0.6556851417861808 
Iteration 32 	 0.6532180746328442 					 0.6556851417861808 
Iteration 33 	 0.6532180746328442 					 0.6556851417861808 
Iteration 34 	 0.6532180746328442 					 0.6556851417861808 
Iteration 35 	 0.6532180746328442 					 0.6556851417861808 
Iteration 36 	 0.6532180746328442 					 0.6556851417861808 
Iteration 37 	 0.6532180746328442 					 0.6556851417861808 
Iteration 38 	 0.6532180746328442 					 0.6556851417861808 
Iteration 39 	 0.6532180746328442 					 0.6556851417861808 
Iteration 40 	 0.6532180746328442 					 0.6556851417861808 
Iteration 41 	 0.6532180746328442 					 0.6556851417861808 
Iteration 42 	 0.6532180746328442 					 0.6556851417861808 
Iteration 43 	 0.6532180746328442 					 0.6556851417861808 
Iteration 44 	 0.6532180746328442 					 0.6556851417861808 
Iteration 45 	 0.6532180746328442 					 0.6556851417861808 
Iteration 46 	 0.6532180746328442 					 0.6556851417861808 
Iteration 47 	 0.6532180746328442 					 0.6556851417861808 
Iteration 48 	 0.6532180746328442 					 0.6556851417861808 
Iteration 49 	 0.6532180746328442 					 0.6556851417861808 


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Run Number - 9
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6414319881877312 					 0.6414319881877312 
Iteration 1 	 0.645082478995986 					 0.645082478995986 
Iteration 2 	 0.6462510705065081 					 0.6462510705065081 
Iteration 3 	 0.645082478995986 					 0.6462510705065081 
Iteration 4 	 0.6474893230931886 					 0.6474893230931886 
Iteration 5 	 0.6490058301968454 					 0.6490058301968454 
Iteration 6 	 0.6528143634912219 					 0.6528143634912219 
Iteration 7 	 0.6533643330017411 					 0.6533643330017411 
Iteration 8 	 0.6528143634912219 					 0.6533643330017411 
Iteration 9 	 0.6574034948788391 					 0.6574034948788391 
Iteration 10 	 0.6536186100004249 					 0.6574034948788391 
Iteration 11 	 0.6536186100004249 					 0.6574034948788391 
Iteration 12 	 0.6536186100004249 					 0.6574034948788391 
Iteration 13 	 0.6536186100004249 					 0.6574034948788391 
Iteration 14 	 0.6544512161480377 					 0.6574034948788391 
Iteration 15 	 0.6544512161480377 					 0.6574034948788391 
Iteration 16 	 0.6544512161480377 					 0.6574034948788391 
Iteration 17 	 0.6544512161480377 					 0.6574034948788391 
Iteration 18 	 0.6544512161480377 					 0.6574034948788391 
Iteration 19 	 0.6544512161480377 					 0.6574034948788391 
Iteration 20 	 0.6544512161480377 					 0.6574034948788391 
Iteration 21 	 0.6544512161480377 					 0.6574034948788391 
Iteration 22 	 0.6544512161480377 					 0.6574034948788391 
Iteration 23 	 0.6544512161480377 					 0.6574034948788391 
Iteration 24 	 0.6544512161480377 					 0.6574034948788391 
Iteration 25 	 0.6544512161480377 					 0.6574034948788391 
Iteration 26 	 0.6544512161480377 					 0.6574034948788391 
Iteration 27 	 0.6544512161480377 					 0.6574034948788391 
Iteration 28 	 0.6544512161480377 					 0.6574034948788391 
Iteration 29 	 0.6544512161480377 					 0.6574034948788391 
Iteration 30 	 0.6544512161480377 					 0.6574034948788391 
Iteration 31 	 0.6544512161480377 					 0.6574034948788391 
Iteration 32 	 0.6544512161480377 					 0.6574034948788391 
Iteration 33 	 0.6544512161480377 					 0.6574034948788391 
Iteration 34 	 0.6544512161480377 					 0.6574034948788391 
Iteration 35 	 0.6544512161480377 					 0.6574034948788391 
Iteration 36 	 0.6544512161480377 					 0.6574034948788391 
Iteration 37 	 0.6544512161480377 					 0.6574034948788391 
Iteration 38 	 0.6544512161480377 					 0.6574034948788391 
Iteration 39 	 0.6544512161480377 					 0.6574034948788391 
Iteration 40 	 0.6544512161480377 					 0.6574034948788391 
Iteration 41 	 0.6544512161480377 					 0.6574034948788391 
Iteration 42 	 0.6544512161480377 					 0.6574034948788391 
Iteration 43 	 0.6544512161480377 					 0.6574034948788391 
Iteration 44 	 0.6544512161480377 					 0.6574034948788391 
Iteration 45 	 0.6544512161480377 					 0.6574034948788391 
Iteration 46 	 0.6544512161480377 					 0.6574034948788391 
Iteration 47 	 0.6544512161480377 					 0.6574034948788391 
Iteration 48 	 0.6544512161480377 					 0.6574034948788391 
Iteration 49 	 0.6544512161480377 					 0.6574034948788391 


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Run Number - 10
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.642609023565132 					 0.642609023565132 
Iteration 1 	 0.6431892120661444 					 0.6431892120661444 
Iteration 2 	 0.645739510790606 					 0.645739510790606 
Iteration 3 	 0.645739510790606 					 0.645739510790606 
Iteration 4 	 0.646388916256737 					 0.646388916256737 
Iteration 5 	 0.6465929975227417 					 0.6465929975227417 
Iteration 6 	 0.6483103833746173 					 0.6483103833746173 
Iteration 7 	 0.6506448958815456 					 0.6506448958815456 
Iteration 8 	 0.6506448958815456 					 0.6506448958815456 
Iteration 9 	 0.6530694337216548 					 0.6530694337216548 
Iteration 10 	 0.6530694337216548 					 0.6530694337216548 
Iteration 11 	 0.6530694337216548 					 0.6530694337216548 
Iteration 12 	 0.6537717194559813 					 0.6537717194559813 
Iteration 13 	 0.6537717194559813 					 0.6537717194559813 
Iteration 14 	 0.6537717194559813 					 0.6537717194559813 
Iteration 15 	 0.6537717194559813 					 0.6537717194559813 
Iteration 16 	 0.6537717194559813 					 0.6537717194559813 
Iteration 17 	 0.6537717194559813 					 0.6537717194559813 
Iteration 18 	 0.6537717194559813 					 0.6537717194559813 
Iteration 19 	 0.6504270079089054 					 0.6537717194559813 
Iteration 20 	 0.6504270079089054 					 0.6537717194559813 
Iteration 21 	 0.6504270079089054 					 0.6537717194559813 
Iteration 22 	 0.6504270079089054 					 0.6537717194559813 
Iteration 23 	 0.6504270079089054 					 0.6537717194559813 
Iteration 24 	 0.6504270079089054 					 0.6537717194559813 
Iteration 25 	 0.6504270079089054 					 0.6537717194559813 
Iteration 26 	 0.6504270079089054 					 0.6537717194559813 
Iteration 27 	 0.6504270079089054 					 0.6537717194559813 
Iteration 28 	 0.6504270079089054 					 0.6537717194559813 
Iteration 29 	 0.6504270079089054 					 0.6537717194559813 
Iteration 30 	 0.6504270079089054 					 0.6537717194559813 
Iteration 31 	 0.6504270079089054 					 0.6537717194559813 
Iteration 32 	 0.6504270079089054 					 0.6537717194559813 
Iteration 33 	 0.6504270079089054 					 0.6537717194559813 
Iteration 34 	 0.6504270079089054 					 0.6537717194559813 
Iteration 35 	 0.6504270079089054 					 0.6537717194559813 
Iteration 36 	 0.6504270079089054 					 0.6537717194559813 
Iteration 37 	 0.6504270079089054 					 0.6537717194559813 
Iteration 38 	 0.6504270079089054 					 0.6537717194559813 
Iteration 39 	 0.6504270079089054 					 0.6537717194559813 
Iteration 40 	 0.6504270079089054 					 0.6537717194559813 
Iteration 41 	 0.6504270079089054 					 0.6537717194559813 
Iteration 42 	 0.6504270079089054 					 0.6537717194559813 
Iteration 43 	 0.6504270079089054 					 0.6537717194559813 
Iteration 44 	 0.6504270079089054 					 0.6537717194559813 
Iteration 45 	 0.6504270079089054 					 0.6537717194559813 
Iteration 46 	 0.6504270079089054 					 0.6537717194559813 
Iteration 47 	 0.6504270079089054 					 0.6537717194559813 
Iteration 48 	 0.6504270079089054 					 0.6537717194559813 
Iteration 49 	 0.6504270079089054 					 0.6537717194559813 


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Run Number - 11
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.641139461362781 					 0.641139461362781 
Iteration 1 	 0.6418367193989378 					 0.6418367193989378 
Iteration 2 	 0.6478588273730918 					 0.6478588273730918 
Iteration 3 	 0.6493256730745285 					 0.6493256730745285 
Iteration 4 	 0.6513849508631264 					 0.6513849508631264 
Iteration 5 	 0.6540134478630818 					 0.6540134478630818 
Iteration 6 	 0.655065201839567 					 0.655065201839567 
Iteration 7 	 0.6584000048860378 					 0.6584000048860378 
Iteration 8 	 0.6589400484694736 					 0.6589400484694736 
Iteration 9 	 0.6613212094837687 					 0.6613212094837687 
Iteration 10 	 0.6635201066508458 					 0.6635201066508458 
Iteration 11 	 0.6618203721085216 					 0.6635201066508458 
Iteration 12 	 0.6635201066508458 					 0.6635201066508458 
Iteration 13 	 0.6639955299991794 					 0.6639955299991794 
Iteration 14 	 0.6628385537171951 					 0.6639955299991794 
Iteration 15 	 0.6628385537171951 					 0.6639955299991794 
Iteration 16 	 0.6628385537171951 					 0.6639955299991794 
Iteration 17 	 0.6628385537171951 					 0.6639955299991794 
Iteration 18 	 0.6628385537171951 					 0.6639955299991794 
Iteration 19 	 0.6629159959556539 					 0.6639955299991794 
Iteration 20 	 0.6629159959556539 					 0.6639955299991794 
Iteration 21 	 0.6629159959556539 					 0.6639955299991794 
Iteration 22 	 0.6629159959556539 					 0.6639955299991794 
Iteration 23 	 0.6629159959556539 					 0.6639955299991794 
Iteration 24 	 0.6629159959556539 					 0.6639955299991794 
Iteration 25 	 0.6629159959556539 					 0.6639955299991794 
Iteration 26 	 0.6629159959556539 					 0.6639955299991794 
Iteration 27 	 0.6629159959556539 					 0.6639955299991794 
Iteration 28 	 0.6629159959556539 					 0.6639955299991794 
Iteration 29 	 0.6629159959556539 					 0.6639955299991794 
Iteration 30 	 0.6629159959556539 					 0.6639955299991794 
Iteration 31 	 0.6629159959556539 					 0.6639955299991794 
Iteration 32 	 0.6629159959556539 					 0.6639955299991794 
Iteration 33 	 0.6629159959556539 					 0.6639955299991794 
Iteration 34 	 0.6629159959556539 					 0.6639955299991794 
Iteration 35 	 0.6629159959556539 					 0.6639955299991794 
Iteration 36 	 0.6629159959556539 					 0.6639955299991794 
Iteration 37 	 0.6629159959556539 					 0.6639955299991794 
Iteration 38 	 0.6629159959556539 					 0.6639955299991794 
Iteration 39 	 0.6629159959556539 					 0.6639955299991794 
Iteration 40 	 0.6629159959556539 					 0.6639955299991794 
Iteration 41 	 0.6629159959556539 					 0.6639955299991794 
Iteration 42 	 0.6629159959556539 					 0.6639955299991794 
Iteration 43 	 0.6629159959556539 					 0.6639955299991794 
Iteration 44 	 0.6629159959556539 					 0.6639955299991794 
Iteration 45 	 0.6629159959556539 					 0.6639955299991794 
Iteration 46 	 0.6629159959556539 					 0.6639955299991794 
Iteration 47 	 0.6629159959556539 					 0.6639955299991794 
Iteration 48 	 0.6629159959556539 					 0.6639955299991794 
Iteration 49 	 0.6629159959556539 					 0.6639955299991794 


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Run Number - 12
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6416400415450342 					 0.6416400415450342 
Iteration 1 	 0.649518660249467 					 0.649518660249467 
Iteration 2 	 0.649518660249467 					 0.649518660249467 
Iteration 3 	 0.6533156637745019 					 0.6533156637745019 
Iteration 4 	 0.6454999360522269 					 0.6533156637745019 
Iteration 5 	 0.6469689658103976 					 0.6533156637745019 
Iteration 6 	 0.6489983348554224 					 0.6533156637745019 
Iteration 7 	 0.6489983348554224 					 0.6533156637745019 
Iteration 8 	 0.6514612324280088 					 0.6533156637745019 
Iteration 9 	 0.6522941161405273 					 0.6533156637745019 
Iteration 10 	 0.6545325407103935 					 0.6545325407103935 
Iteration 11 	 0.6545325407103935 					 0.6545325407103935 
Iteration 12 	 0.6545325407103935 					 0.6545325407103935 
Iteration 13 	 0.6568236616146716 					 0.6568236616146716 
Iteration 14 	 0.6567524080808834 					 0.6568236616146716 
Iteration 15 	 0.6567524080808834 					 0.6568236616146716 
Iteration 16 	 0.6567524080808834 					 0.6568236616146716 
Iteration 17 	 0.6567524080808834 					 0.6568236616146716 
Iteration 18 	 0.6567524080808834 					 0.6568236616146716 
Iteration 19 	 0.6567524080808834 					 0.6568236616146716 
Iteration 20 	 0.6567524080808834 					 0.6568236616146716 
Iteration 21 	 0.6567524080808834 					 0.6568236616146716 
Iteration 22 	 0.6567524080808834 					 0.6568236616146716 
Iteration 23 	 0.6567524080808834 					 0.6568236616146716 
Iteration 24 	 0.6567524080808834 					 0.6568236616146716 
Iteration 25 	 0.6567524080808834 					 0.6568236616146716 
Iteration 26 	 0.6567524080808834 					 0.6568236616146716 
Iteration 27 	 0.6567524080808834 					 0.6568236616146716 
Iteration 28 	 0.6567524080808834 					 0.6568236616146716 
Iteration 29 	 0.6567524080808834 					 0.6568236616146716 
Iteration 30 	 0.6567524080808834 					 0.6568236616146716 
Iteration 31 	 0.6567524080808834 					 0.6568236616146716 
Iteration 32 	 0.6567524080808834 					 0.6568236616146716 
Iteration 33 	 0.6567524080808834 					 0.6568236616146716 
Iteration 34 	 0.6567524080808834 					 0.6568236616146716 
Iteration 35 	 0.6567524080808834 					 0.6568236616146716 
Iteration 36 	 0.6567524080808834 					 0.6568236616146716 
Iteration 37 	 0.6567524080808834 					 0.6568236616146716 
Iteration 38 	 0.6567524080808834 					 0.6568236616146716 
Iteration 39 	 0.6567524080808834 					 0.6568236616146716 
Iteration 40 	 0.6567524080808834 					 0.6568236616146716 
Iteration 41 	 0.6567524080808834 					 0.6568236616146716 
Iteration 42 	 0.6567524080808834 					 0.6568236616146716 
Iteration 43 	 0.6567524080808834 					 0.6568236616146716 
Iteration 44 	 0.6567524080808834 					 0.6568236616146716 
Iteration 45 	 0.6567524080808834 					 0.6568236616146716 
Iteration 46 	 0.6567524080808834 					 0.6568236616146716 
Iteration 47 	 0.6567524080808834 					 0.6568236616146716 
Iteration 48 	 0.6567524080808834 					 0.6568236616146716 
Iteration 49 	 0.6567524080808834 					 0.6568236616146716 


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Run Number - 13
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6445747893016867 					 0.6445747893016867 
Iteration 1 	 0.646789245280396 					 0.646789245280396 
Iteration 2 	 0.6440507568885905 					 0.646789245280396 
Iteration 3 	 0.6453871044046116 					 0.646789245280396 
Iteration 4 	 0.6473251333267379 					 0.6473251333267379 
Iteration 5 	 0.6486934250294334 					 0.6486934250294334 
Iteration 6 	 0.6489737512952894 					 0.6489737512952894 
Iteration 7 	 0.6522330685844033 					 0.6522330685844033 
Iteration 8 	 0.6501080685635976 					 0.6522330685844033 
Iteration 9 	 0.6582200565047052 					 0.6582200565047052 
Iteration 10 	 0.6582200565047052 					 0.6582200565047052 
Iteration 11 	 0.6582200565047052 					 0.6582200565047052 
Iteration 12 	 0.6612745524586767 					 0.6612745524586767 
Iteration 13 	 0.6612745524586767 					 0.6612745524586767 
Iteration 14 	 0.6612745524586767 					 0.6612745524586767 
Iteration 15 	 0.6612745524586767 					 0.6612745524586767 
Iteration 16 	 0.6612745524586767 					 0.6612745524586767 
Iteration 17 	 0.6612745524586767 					 0.6612745524586767 
Iteration 18 	 0.6612745524586767 					 0.6612745524586767 
Iteration 19 	 0.6612745524586767 					 0.6612745524586767 
Iteration 20 	 0.6612745524586767 					 0.6612745524586767 
Iteration 21 	 0.6612745524586767 					 0.6612745524586767 
Iteration 22 	 0.6612745524586767 					 0.6612745524586767 
Iteration 23 	 0.6612745524586767 					 0.6612745524586767 
Iteration 24 	 0.6612745524586767 					 0.6612745524586767 
Iteration 25 	 0.6612745524586767 					 0.6612745524586767 
Iteration 26 	 0.6612745524586767 					 0.6612745524586767 
Iteration 27 	 0.6612745524586767 					 0.6612745524586767 
Iteration 28 	 0.6612745524586767 					 0.6612745524586767 
Iteration 29 	 0.6612745524586767 					 0.6612745524586767 
Iteration 30 	 0.6612745524586767 					 0.6612745524586767 
Iteration 31 	 0.6612745524586767 					 0.6612745524586767 
Iteration 32 	 0.6612745524586767 					 0.6612745524586767 
Iteration 33 	 0.6612745524586767 					 0.6612745524586767 
Iteration 34 	 0.6612745524586767 					 0.6612745524586767 
Iteration 35 	 0.6612745524586767 					 0.6612745524586767 
Iteration 36 	 0.6612745524586767 					 0.6612745524586767 
Iteration 37 	 0.6612745524586767 					 0.6612745524586767 
Iteration 38 	 0.6612745524586767 					 0.6612745524586767 
Iteration 39 	 0.6612745524586767 					 0.6612745524586767 
Iteration 40 	 0.6612745524586767 					 0.6612745524586767 
Iteration 41 	 0.6612745524586767 					 0.6612745524586767 
Iteration 42 	 0.6612745524586767 					 0.6612745524586767 
Iteration 43 	 0.6612745524586767 					 0.6612745524586767 
Iteration 44 	 0.6612745524586767 					 0.6612745524586767 
Iteration 45 	 0.6612745524586767 					 0.6612745524586767 
Iteration 46 	 0.6612745524586767 					 0.6612745524586767 
Iteration 47 	 0.6612745524586767 					 0.6612745524586767 
Iteration 48 	 0.6612745524586767 					 0.6612745524586767 
Iteration 49 	 0.6612745524586767 					 0.6612745524586767 


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Run Number - 14
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6496236584145413 					 0.6496236584145413 
Iteration 1 	 0.6487200607646306 					 0.6496236584145413 
Iteration 2 	 0.6453688658854047 					 0.6496236584145413 
Iteration 3 	 0.6449859479028301 					 0.6496236584145413 
Iteration 4 	 0.6469351366297383 					 0.6496236584145413 
Iteration 5 	 0.6504735045017649 					 0.6504735045017649 
Iteration 6 	 0.6510315121754712 					 0.6510315121754712 
Iteration 7 	 0.6510315121754712 					 0.6510315121754712 
Iteration 8 	 0.6522049544105715 					 0.6522049544105715 
Iteration 9 	 0.6522049544105715 					 0.6522049544105715 
Iteration 10 	 0.6522049544105715 					 0.6522049544105715 
Iteration 11 	 0.6522049544105715 					 0.6522049544105715 
Iteration 12 	 0.6535347247883633 					 0.6535347247883633 
Iteration 13 	 0.6535347247883633 					 0.6535347247883633 
Iteration 14 	 0.6535347247883633 					 0.6535347247883633 
Iteration 15 	 0.6535347247883633 					 0.6535347247883633 
Iteration 16 	 0.6535347247883633 					 0.6535347247883633 
Iteration 17 	 0.6535347247883633 					 0.6535347247883633 
Iteration 18 	 0.6535347247883633 					 0.6535347247883633 
Iteration 19 	 0.6535347247883633 					 0.6535347247883633 
Iteration 20 	 0.6535347247883633 					 0.6535347247883633 
Iteration 21 	 0.6535347247883633 					 0.6535347247883633 
Iteration 22 	 0.6535347247883633 					 0.6535347247883633 
Iteration 23 	 0.6535347247883633 					 0.6535347247883633 
Iteration 24 	 0.6535347247883633 					 0.6535347247883633 
Iteration 25 	 0.6535347247883633 					 0.6535347247883633 
Iteration 26 	 0.6535347247883633 					 0.6535347247883633 
Iteration 27 	 0.6535347247883633 					 0.6535347247883633 
Iteration 28 	 0.6535347247883633 					 0.6535347247883633 
Iteration 29 	 0.6535347247883633 					 0.6535347247883633 
Iteration 30 	 0.6535347247883633 					 0.6535347247883633 
Iteration 31 	 0.6535347247883633 					 0.6535347247883633 
Iteration 32 	 0.6535347247883633 					 0.6535347247883633 
Iteration 33 	 0.6535347247883633 					 0.6535347247883633 
Iteration 34 	 0.6535347247883633 					 0.6535347247883633 
Iteration 35 	 0.6535347247883633 					 0.6535347247883633 
Iteration 36 	 0.6535347247883633 					 0.6535347247883633 
Iteration 37 	 0.6535347247883633 					 0.6535347247883633 
Iteration 38 	 0.6535347247883633 					 0.6535347247883633 
Iteration 39 	 0.6535347247883633 					 0.6535347247883633 
Iteration 40 	 0.6535347247883633 					 0.6535347247883633 
Iteration 41 	 0.6535347247883633 					 0.6535347247883633 
Iteration 42 	 0.6535347247883633 					 0.6535347247883633 
Iteration 43 	 0.6535347247883633 					 0.6535347247883633 
Iteration 44 	 0.6535347247883633 					 0.6535347247883633 
Iteration 45 	 0.6535347247883633 					 0.6535347247883633 
Iteration 46 	 0.6535347247883633 					 0.6535347247883633 
Iteration 47 	 0.6535347247883633 					 0.6535347247883633 
Iteration 48 	 0.6535347247883633 					 0.6535347247883633 
Iteration 49 	 0.6535347247883633 					 0.6535347247883633 


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Run Number - 15
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6471884669769828 					 0.6471884669769828 
Iteration 1 	 0.6494784534435719 					 0.6494784534435719 
Iteration 2 	 0.6498134162446498 					 0.6498134162446498 
Iteration 3 	 0.6548838072495511 					 0.6548838072495511 
Iteration 4 	 0.652321523908616 					 0.6548838072495511 
Iteration 5 	 0.6509401781323536 					 0.6548838072495511 
Iteration 6 	 0.6495397251113912 					 0.6548838072495511 
Iteration 7 	 0.6527448786987817 					 0.6548838072495511 
Iteration 8 	 0.6540833595480551 					 0.6548838072495511 
Iteration 9 	 0.6572128238606073 					 0.6572128238606073 
Iteration 10 	 0.659449711855529 					 0.659449711855529 
Iteration 11 	 0.659449711855529 					 0.659449711855529 
Iteration 12 	 0.659449711855529 					 0.659449711855529 
Iteration 13 	 0.6600186426364787 					 0.6600186426364787 
Iteration 14 	 0.6600186426364787 					 0.6600186426364787 
Iteration 15 	 0.6608799239517493 					 0.6608799239517493 
Iteration 16 	 0.6608799239517493 					 0.6608799239517493 
Iteration 17 	 0.6608799239517493 					 0.6608799239517493 
Iteration 18 	 0.6608799239517493 					 0.6608799239517493 
Iteration 19 	 0.6608799239517493 					 0.6608799239517493 
Iteration 20 	 0.66146347949262 					 0.66146347949262 
Iteration 21 	 0.6608799239517493 					 0.66146347949262 
Iteration 22 	 0.6608799239517493 					 0.66146347949262 
Iteration 23 	 0.6608799239517493 					 0.66146347949262 
Iteration 24 	 0.6608799239517493 					 0.66146347949262 
Iteration 25 	 0.6608799239517493 					 0.66146347949262 
Iteration 26 	 0.6608799239517493 					 0.66146347949262 
Iteration 27 	 0.6608799239517493 					 0.66146347949262 
Iteration 28 	 0.6608799239517493 					 0.66146347949262 
Iteration 29 	 0.6608799239517493 					 0.66146347949262 
Iteration 30 	 0.6608799239517493 					 0.66146347949262 
Iteration 31 	 0.6608799239517493 					 0.66146347949262 
Iteration 32 	 0.6608799239517493 					 0.66146347949262 
Iteration 33 	 0.6608799239517493 					 0.66146347949262 
Iteration 34 	 0.6608799239517493 					 0.66146347949262 
Iteration 35 	 0.6608799239517493 					 0.66146347949262 
Iteration 36 	 0.6608799239517493 					 0.66146347949262 
Iteration 37 	 0.6608799239517493 					 0.66146347949262 
Iteration 38 	 0.6608799239517493 					 0.66146347949262 
Iteration 39 	 0.6608799239517493 					 0.66146347949262 
Iteration 40 	 0.6608799239517493 					 0.66146347949262 
Iteration 41 	 0.6608799239517493 					 0.66146347949262 
Iteration 42 	 0.6608799239517493 					 0.66146347949262 
Iteration 43 	 0.6608799239517493 					 0.66146347949262 
Iteration 44 	 0.6608799239517493 					 0.66146347949262 
Iteration 45 	 0.6608799239517493 					 0.66146347949262 
Iteration 46 	 0.6608799239517493 					 0.66146347949262 
Iteration 47 	 0.6608799239517493 					 0.66146347949262 
Iteration 48 	 0.6608799239517493 					 0.66146347949262 
Iteration 49 	 0.6608799239517493 					 0.66146347949262 


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Run Number - 16
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6443844953926677 					 0.6443844953926677 
Iteration 1 	 0.641005631654574 					 0.6443844953926677 
Iteration 2 	 0.6452960719132529 					 0.6452960719132529 
Iteration 3 	 0.6508183482658395 					 0.6508183482658395 
Iteration 4 	 0.6491597441640063 					 0.6508183482658395 
Iteration 5 	 0.6491597441640063 					 0.6508183482658395 
Iteration 6 	 0.6526334311447192 					 0.6526334311447192 
Iteration 7 	 0.654419046741313 					 0.654419046741313 
Iteration 8 	 0.6556318775628717 					 0.6556318775628717 
Iteration 9 	 0.6556318775628717 					 0.6556318775628717 
Iteration 10 	 0.6569645022807156 					 0.6569645022807156 
Iteration 11 	 0.6569645022807156 					 0.6569645022807156 
Iteration 12 	 0.657182882487571 					 0.657182882487571 
Iteration 13 	 0.6572615490229478 					 0.6572615490229478 
Iteration 14 	 0.6572615490229478 					 0.6572615490229478 
Iteration 15 	 0.6572615490229478 					 0.6572615490229478 
Iteration 16 	 0.6572615490229478 					 0.6572615490229478 
Iteration 17 	 0.6582217869571502 					 0.6582217869571502 
Iteration 18 	 0.6582217869571502 					 0.6582217869571502 
Iteration 19 	 0.6582217869571502 					 0.6582217869571502 
Iteration 20 	 0.6582217869571502 					 0.6582217869571502 
Iteration 21 	 0.6582217869571502 					 0.6582217869571502 
Iteration 22 	 0.6582217869571502 					 0.6582217869571502 
Iteration 23 	 0.6582217869571502 					 0.6582217869571502 
Iteration 24 	 0.6582217869571502 					 0.6582217869571502 
Iteration 25 	 0.6582217869571502 					 0.6582217869571502 
Iteration 26 	 0.6582217869571502 					 0.6582217869571502 
Iteration 27 	 0.6582217869571502 					 0.6582217869571502 
Iteration 28 	 0.6582217869571502 					 0.6582217869571502 
Iteration 29 	 0.6582217869571502 					 0.6582217869571502 
Iteration 30 	 0.6582217869571502 					 0.6582217869571502 
Iteration 31 	 0.6582217869571502 					 0.6582217869571502 
Iteration 32 	 0.6582217869571502 					 0.6582217869571502 
Iteration 33 	 0.6582217869571502 					 0.6582217869571502 
Iteration 34 	 0.6582217869571502 					 0.6582217869571502 
Iteration 35 	 0.6582217869571502 					 0.6582217869571502 
Iteration 36 	 0.6582217869571502 					 0.6582217869571502 
Iteration 37 	 0.6582217869571502 					 0.6582217869571502 
Iteration 38 	 0.6582217869571502 					 0.6582217869571502 
Iteration 39 	 0.6582217869571502 					 0.6582217869571502 
Iteration 40 	 0.6582217869571502 					 0.6582217869571502 
Iteration 41 	 0.6582217869571502 					 0.6582217869571502 
Iteration 42 	 0.6582217869571502 					 0.6582217869571502 
Iteration 43 	 0.6582217869571502 					 0.6582217869571502 
Iteration 44 	 0.6582217869571502 					 0.6582217869571502 
Iteration 45 	 0.6582217869571502 					 0.6582217869571502 
Iteration 46 	 0.6582217869571502 					 0.6582217869571502 
Iteration 47 	 0.6582217869571502 					 0.6582217869571502 
Iteration 48 	 0.6582217869571502 					 0.6582217869571502 
Iteration 49 	 0.6582217869571502 					 0.6582217869571502 


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Run Number - 17
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6387345865109916 					 0.6387345865109916 
Iteration 1 	 0.6401989794918852 					 0.6401989794918852 
Iteration 2 	 0.6436890879616263 					 0.6436890879616263 
Iteration 3 	 0.6426970227162327 					 0.6436890879616263 
Iteration 4 	 0.6446211396795778 					 0.6446211396795778 
Iteration 5 	 0.6454942994249296 					 0.6454942994249296 
Iteration 6 	 0.6454942994249296 					 0.6454942994249296 
Iteration 7 	 0.6473071537904055 					 0.6473071537904055 
Iteration 8 	 0.6490094040932589 					 0.6490094040932589 
Iteration 9 	 0.6503907264726175 					 0.6503907264726175 
Iteration 10 	 0.6519905263068441 					 0.6519905263068441 
Iteration 11 	 0.6516111102723993 					 0.6519905263068441 
Iteration 12 	 0.6521081906467451 					 0.6521081906467451 
Iteration 13 	 0.6570176779954019 					 0.6570176779954019 
Iteration 14 	 0.6570176779954019 					 0.6570176779954019 
Iteration 15 	 0.6570176779954019 					 0.6570176779954019 
Iteration 16 	 0.6553408716428067 					 0.6570176779954019 
Iteration 17 	 0.6591514147819042 					 0.6591514147819042 
Iteration 18 	 0.6575444310172631 					 0.6591514147819042 
Iteration 19 	 0.6600330114614155 					 0.6600330114614155 
Iteration 20 	 0.6600330114614155 					 0.6600330114614155 
Iteration 21 	 0.6629722296623501 					 0.6629722296623501 
Iteration 22 	 0.6629722296623501 					 0.6629722296623501 
Iteration 23 	 0.6629722296623501 					 0.6629722296623501 
Iteration 24 	 0.6629722296623501 					 0.6629722296623501 
Iteration 25 	 0.6629722296623501 					 0.6629722296623501 
Iteration 26 	 0.6629722296623501 					 0.6629722296623501 
Iteration 27 	 0.6629722296623501 					 0.6629722296623501 
Iteration 28 	 0.6629722296623501 					 0.6629722296623501 
Iteration 29 	 0.6629722296623501 					 0.6629722296623501 
Iteration 30 	 0.6629722296623501 					 0.6629722296623501 
Iteration 31 	 0.6629722296623501 					 0.6629722296623501 
Iteration 32 	 0.6629722296623501 					 0.6629722296623501 
Iteration 33 	 0.6629722296623501 					 0.6629722296623501 
Iteration 34 	 0.6629722296623501 					 0.6629722296623501 
Iteration 35 	 0.6629722296623501 					 0.6629722296623501 
Iteration 36 	 0.6629722296623501 					 0.6629722296623501 
Iteration 37 	 0.6629722296623501 					 0.6629722296623501 
Iteration 38 	 0.6629722296623501 					 0.6629722296623501 
Iteration 39 	 0.6629722296623501 					 0.6629722296623501 
Iteration 40 	 0.6629722296623501 					 0.6629722296623501 
Iteration 41 	 0.6629722296623501 					 0.6629722296623501 
Iteration 42 	 0.6629722296623501 					 0.6629722296623501 
Iteration 43 	 0.6629722296623501 					 0.6629722296623501 
Iteration 44 	 0.6629722296623501 					 0.6629722296623501 
Iteration 45 	 0.6629722296623501 					 0.6629722296623501 
Iteration 46 	 0.6629722296623501 					 0.6629722296623501 
Iteration 47 	 0.6629722296623501 					 0.6629722296623501 
Iteration 48 	 0.6629722296623501 					 0.6629722296623501 
Iteration 49 	 0.6629722296623501 					 0.6629722296623501 


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Run Number - 18
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6492259889982032 					 0.6492259889982032 
Iteration 1 	 0.6497764105082314 					 0.6497764105082314 
Iteration 2 	 0.6501090428059783 					 0.6501090428059783 
Iteration 3 	 0.6467933357006129 					 0.6501090428059783 
Iteration 4 	 0.6499193902330308 					 0.6501090428059783 
Iteration 5 	 0.6518852499791756 					 0.6518852499791756 
Iteration 6 	 0.6546124348580981 					 0.6546124348580981 
Iteration 7 	 0.6546124348580981 					 0.6546124348580981 
Iteration 8 	 0.6546124348580981 					 0.6546124348580981 
Iteration 9 	 0.6549812543709377 					 0.6549812543709377 
Iteration 10 	 0.6549812543709377 					 0.6549812543709377 
Iteration 11 	 0.6574231547858701 					 0.6574231547858701 
Iteration 12 	 0.6574231547858701 					 0.6574231547858701 
Iteration 13 	 0.6581110011970518 					 0.6581110011970518 
Iteration 14 	 0.658489883830227 					 0.658489883830227 
Iteration 15 	 0.658489883830227 					 0.658489883830227 
Iteration 16 	 0.658489883830227 					 0.658489883830227 
Iteration 17 	 0.6584066908013686 					 0.658489883830227 
Iteration 18 	 0.6584066908013686 					 0.658489883830227 
Iteration 19 	 0.6584066908013686 					 0.658489883830227 
Iteration 20 	 0.6584066908013686 					 0.658489883830227 
Iteration 21 	 0.6584066908013686 					 0.658489883830227 
Iteration 22 	 0.6584066908013686 					 0.658489883830227 
Iteration 23 	 0.6584066908013686 					 0.658489883830227 
Iteration 24 	 0.6584066908013686 					 0.658489883830227 
Iteration 25 	 0.6584066908013686 					 0.658489883830227 
Iteration 26 	 0.6584066908013686 					 0.658489883830227 
Iteration 27 	 0.6584066908013686 					 0.658489883830227 
Iteration 28 	 0.6584066908013686 					 0.658489883830227 
Iteration 29 	 0.6584066908013686 					 0.658489883830227 
Iteration 30 	 0.6584066908013686 					 0.658489883830227 
Iteration 31 	 0.6584066908013686 					 0.658489883830227 
Iteration 32 	 0.6584066908013686 					 0.658489883830227 
Iteration 33 	 0.6584066908013686 					 0.658489883830227 
Iteration 34 	 0.6584066908013686 					 0.658489883830227 
Iteration 35 	 0.6584066908013686 					 0.658489883830227 
Iteration 36 	 0.6584066908013686 					 0.658489883830227 
Iteration 37 	 0.6584066908013686 					 0.658489883830227 
Iteration 38 	 0.6584066908013686 					 0.658489883830227 
Iteration 39 	 0.6584066908013686 					 0.658489883830227 
Iteration 40 	 0.6584066908013686 					 0.658489883830227 
Iteration 41 	 0.6584066908013686 					 0.658489883830227 
Iteration 42 	 0.6584066908013686 					 0.658489883830227 
Iteration 43 	 0.6584066908013686 					 0.658489883830227 
Iteration 44 	 0.6584066908013686 					 0.658489883830227 
Iteration 45 	 0.6584066908013686 					 0.658489883830227 
Iteration 46 	 0.6584066908013686 					 0.658489883830227 
Iteration 47 	 0.6584066908013686 					 0.658489883830227 
Iteration 48 	 0.6584066908013686 					 0.658489883830227 
Iteration 49 	 0.6584066908013686 					 0.658489883830227 


 ----------------------------------------------------------------------------------------
Run Number - 19
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.6361137953482172 					 0.6361137953482172 
Iteration 1 	 0.6420456043572903 					 0.6420456043572903 
Iteration 2 	 0.6452222940035628 					 0.6452222940035628 
Iteration 3 	 0.6452222940035628 					 0.6452222940035628 
Iteration 4 	 0.6452889965828909 					 0.6452889965828909 
Iteration 5 	 0.6449189058057111 					 0.6452889965828909 
Iteration 6 	 0.6482946812063912 					 0.6482946812063912 
Iteration 7 	 0.6474878369286835 					 0.6482946812063912 
Iteration 8 	 0.6476097626983309 					 0.6482946812063912 
Iteration 9 	 0.6476097626983309 					 0.6482946812063912 
Iteration 10 	 0.6488073834623829 					 0.6488073834623829 
Iteration 11 	 0.6490857931571127 					 0.6490857931571127 
Iteration 12 	 0.6490857931571127 					 0.6490857931571127 
Iteration 13 	 0.6497095247117043 					 0.6497095247117043 
Iteration 14 	 0.6497095247117043 					 0.6497095247117043 
Iteration 15 	 0.6497095247117043 					 0.6497095247117043 
Iteration 16 	 0.6517602857761879 					 0.6517602857761879 
Iteration 17 	 0.6517602857761879 					 0.6517602857761879 
Iteration 18 	 0.6529536735261342 					 0.6529536735261342 
Iteration 19 	 0.6529536735261342 					 0.6529536735261342 
Iteration 20 	 0.6529536735261342 					 0.6529536735261342 
Iteration 21 	 0.6529536735261342 					 0.6529536735261342 
Iteration 22 	 0.6529536735261342 					 0.6529536735261342 
Iteration 23 	 0.6529536735261342 					 0.6529536735261342 
Iteration 24 	 0.6529536735261342 					 0.6529536735261342 
Iteration 25 	 0.6529536735261342 					 0.6529536735261342 
Iteration 26 	 0.6529536735261342 					 0.6529536735261342 
Iteration 27 	 0.6529536735261342 					 0.6529536735261342 
Iteration 28 	 0.6529536735261342 					 0.6529536735261342 
Iteration 29 	 0.6529536735261342 					 0.6529536735261342 
Iteration 30 	 0.6529536735261342 					 0.6529536735261342 
Iteration 31 	 0.6529536735261342 					 0.6529536735261342 
Iteration 32 	 0.6529536735261342 					 0.6529536735261342 
Iteration 33 	 0.6529536735261342 					 0.6529536735261342 
Iteration 34 	 0.6529536735261342 					 0.6529536735261342 
Iteration 35 	 0.6529536735261342 					 0.6529536735261342 
Iteration 36 	 0.6529536735261342 					 0.6529536735261342 
Iteration 37 	 0.6529536735261342 					 0.6529536735261342 
Iteration 38 	 0.6529536735261342 					 0.6529536735261342 
Iteration 39 	 0.6529536735261342 					 0.6529536735261342 
Iteration 40 	 0.6529536735261342 					 0.6529536735261342 
Iteration 41 	 0.6529536735261342 					 0.6529536735261342 
Iteration 42 	 0.6529536735261342 					 0.6529536735261342 
Iteration 43 	 0.6529536735261342 					 0.6529536735261342 
Iteration 44 	 0.6529536735261342 					 0.6529536735261342 
Iteration 45 	 0.6529536735261342 					 0.6529536735261342 
Iteration 46 	 0.6529536735261342 					 0.6529536735261342 
Iteration 47 	 0.6529536735261342 					 0.6529536735261342 
Iteration 48 	 0.6529536735261342 					 0.6529536735261342 
Iteration 49 	 0.6529536735261342 					 0.6529536735261342 


 ----------------------------------------------------------------------------------------
Run Number - 20
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.640092460500481 					 0.640092460500481 
Iteration 1 	 0.6498692549743975 					 0.6498692549743975 
Iteration 2 	 0.6466306275156297 					 0.6498692549743975 
Iteration 3 	 0.6479235723606445 					 0.6498692549743975 
Iteration 4 	 0.6529165176279803 					 0.6529165176279803 
Iteration 5 	 0.6611595489388765 					 0.6611595489388765 
Iteration 6 	 0.6565843936217074 					 0.6611595489388765 
Iteration 7 	 0.6555309509156758 					 0.6611595489388765 
Iteration 8 	 0.6555309509156758 					 0.6611595489388765 
Iteration 9 	 0.6565843936217074 					 0.6611595489388765 
Iteration 10 	 0.6611983146029782 					 0.6611983146029782 
Iteration 11 	 0.6624144935609708 					 0.6624144935609708 
Iteration 12 	 0.6633507498600018 					 0.6633507498600018 
Iteration 13 	 0.6633507498600018 					 0.6633507498600018 
Iteration 14 	 0.6642722970415573 					 0.6642722970415573 
Iteration 15 	 0.6640680615480681 					 0.6642722970415573 
Iteration 16 	 0.6649479047503188 					 0.6649479047503188 
Iteration 17 	 0.6649479047503188 					 0.6649479047503188 
Iteration 18 	 0.6660167783129438 					 0.6660167783129438 
Iteration 19 	 0.6660167783129438 					 0.6660167783129438 
Iteration 20 	 0.6662100136743369 					 0.6662100136743369 
Iteration 21 	 0.6662100136743369 					 0.6662100136743369 
Iteration 22 	 0.6662100136743369 					 0.6662100136743369 
Iteration 23 	 0.6662100136743369 					 0.6662100136743369 
Iteration 24 	 0.6662100136743369 					 0.6662100136743369 
Iteration 25 	 0.6662100136743369 					 0.6662100136743369 
Iteration 26 	 0.6662100136743369 					 0.6662100136743369 
Iteration 27 	 0.6662100136743369 					 0.6662100136743369 
Iteration 28 	 0.6662100136743369 					 0.6662100136743369 
Iteration 29 	 0.6662100136743369 					 0.6662100136743369 
Iteration 30 	 0.6662100136743369 					 0.6662100136743369 
Iteration 31 	 0.6662100136743369 					 0.6662100136743369 
Iteration 32 	 0.6662100136743369 					 0.6662100136743369 
Iteration 33 	 0.6662100136743369 					 0.6662100136743369 
Iteration 34 	 0.6662100136743369 					 0.6662100136743369 
Iteration 35 	 0.6662100136743369 					 0.6662100136743369 
Iteration 36 	 0.6662100136743369 					 0.6662100136743369 
Iteration 37 	 0.6662100136743369 					 0.6662100136743369 
Iteration 38 	 0.6662100136743369 					 0.6662100136743369 
Iteration 39 	 0.6662100136743369 					 0.6662100136743369 
Iteration 40 	 0.6662100136743369 					 0.6662100136743369 
Iteration 41 	 0.6662100136743369 					 0.6662100136743369 
Iteration 42 	 0.6662100136743369 					 0.6662100136743369 
Iteration 43 	 0.6662100136743369 					 0.6662100136743369 
Iteration 44 	 0.6662100136743369 					 0.6662100136743369 
Iteration 45 	 0.6662100136743369 					 0.6662100136743369 
Iteration 46 	 0.6662100136743369 					 0.6662100136743369 
Iteration 47 	 0.6662100136743369 					 0.6662100136743369 
Iteration 48 	 0.6662100136743369 					 0.6662100136743369 
Iteration 49 	 0.6662100136743369 					 0.6662100136743369


solutions_rbf['best_solution']

{'run_id': 20,
 'best_score': 0.6662100136743369,
 'num_features': 251,
 'selected_features': ['AMR',
  'naAromAtom',
  'nAtom',
  'nC',
  'nN',
  'nS',
  'nX',
  'ATS2m',
  'ATS5m',
  'ATS6m',
  'ATS0v',
  'ATS3v',
  'ATS4v',
  'ATS5v',
  'ATS6v',
  'ATS1e',
  'ATS4e',
  'ATS7e',
  'ATS8e',
  'ATS0p',
  'ATS4p',
  'ATS5p',
  'ATS7p',
  'ATS0i',
  'ATS1i',
  'ATS3i',
  'ATS5i',
  'ATS6i',
  'ATS7i',
  'ATS1s',
  'ATS4s',
  'ATS6s',
  'AATS0m',
  'AATS2m',
  'AATS4m',
  'AATS5m',
  'AATS7m',
  'AATS0v',
  'AATS1v',
  'AATS2v',
  'AATS3v',
  'AATS5v',
  'AATS8v',
  'AATS0i',
  'AATS2i',
  'AATS3i',
  'AATS4i',
  'AATS5i',
  'AATS6i',
  'AATS2s',
  'AATS4s',
  'AATS5s',
  'AATS7s',
  'ATSC1m',
  'ATSC2m',
  'ATSC3m',
  'ATSC4m',
  'ATSC7m',
  'ATSC1v',
  'ATSC4v',
  'ATSC8v',
  'ATSC0e',
  'ATSC7e',
  'ATSC0p',
  'ATSC6p',
  'ATSC7p',
  'ATSC2i',
  'ATSC6i',
  'ATSC8i',
  'ATSC0s',
  'ATSC3s',
  'ATSC6s',
  'ATSC7s',
  'AATSC0m',
  'AATSC2m',
  'AATSC3m',
  'AATSC8m',
  'AATSC0v',
  'AATSC5v',
  'AATSC0s',
  'SpMAD_DzZ',
  'VR1_DzZ',
  'SpAbs_Dzm',
  'SpDiam_Dzm',
  'EE_Dzm',
  'SM1_Dzm',
  'SpAbs_Dzv',
  'SpMAD_Dzv',
  'EE_Dzv',
  'SM1_Dzv',
  'VR2_Dzv',
  'SpAbs_Dze',
  'EE_Dze',
  'VR2_Dze',
  'EE_Dzp',
  'SM1_Dzp',
  'VE3_Dzp',
  'SpMAD_Dzi',
  'EE_Dzi',
  'SpAbs_Dzs',
  'SpDiam_Dzs',
  'SpMAD_Dzs',
  'SM1_Dzs',
  'VR1_Dzs',
  'VR3_Dzs',
  'BCUTw-1h',
  'BCUTp-1l',
  'BCUTp-1h',
  'nBonds2',
  'nBondsS2',
  'nBondsS3',
  'nBondsD',
  'nBondsM',
  'C1SP2',
  'C3SP2',
  'C3SP3',
  'SPC-5',
  'VPC-4',
  'VPC-5',
  'SP-5',
  'VP-0',
  'VP-1',
  'VP-2',
  'VP-4',
  'VP-5',
  'VP-6',
  'Sare',
  'SpMax_Dt',
  'SpDiam_Dt',
  'SpAD_Dt',
  'SpMAD_Dt',
  'VE3_Dt',
  'VR1_Dt',
  'VR2_Dt',
  'nHBd',
  'nHBint2',
  'nHBint3',
  'nHBint7',
  'nHBint10',
  'nHsOH',
  'nHssNH',
  'nHaaCH',
  'nHCsats',
  'nHCsatu',
  'nHother',
  'ndsCH',
  'nsssCH',
  'ndssC',
  'naaaC',
  'nssNH',
  'naaN',
  'nsssN',
  'nssO',
  'SHBa',
  'SwHBa',
  'SHBint4',
  'SHBint5',
  'SHBint9',
  'SHCsatu',
  'SssCH2',
  'SdsCH',
  'SaaCH',
  'SsssCH',
  'SdssC',
  'SaaaC',
  'SssssC',
  'SsNH2',
  'SdNH',
  'SssNH',
  'SdsN',
  'SaaN',
  'SssO',
  'SaaO',
  'minHBa',
  'minHBint4',
  'minHBint7',
  'minHBint10',
  'mindsCH',
  'minsNH2',
  'minssNH',
  'minaaN',
  'minsssN',
  'minsOH',
  'minssO',
  'minaaO',
  'minsOm',
  'minddssS',
  'maxHBa',
  'maxHBint2',
  'maxHBint3',
  'maxdsCH',
  'maxsNH2',
  'maxssNH',
  'maxaaN',
  'maxsOH',
  'maxdO',
  'maxssO',
  'maxaaO',
  'maxsF',
  'gmax',
  'MAXDP',
  'DELS',
  'MAXDN2',
  'MAXDP2',
  'DELS2',
  'ETA_Beta_ns',
  'ETA_dBeta',
  'ETA_Eta',
  'ETA_Eta_F_L',
  'fragC',
  'nHBAcc3',
  'TIC0',
  'TIC2',
  'TIC4',
  'MIC1',
  'MIC2',
  'ZMIC0',
  'ZMIC5',
  'nAtomLC',
  'nAtomLAC',
  'McGowan_Volume',
  'MDEC-12',
  'MDEC-13',
  'MDEC-22',
  'MDEO-11',
  'MDEN-22',
  'MLFER_BH',
  'MLFER_BO',
  'MPC2',
  'MPC5',
  'MPC6',
  'MPC7',
  'MPC8',
  'MPC9',
  'piPC8',
  'piPC9',
  'R_TpiPCTPC',
  'nRing',
  'nFRing',
  'nFG12Ring',
  'nT10Ring',
  'nRotBt',
  'topoRadius',
  'GGI2',
  'SpAD_D',
  'VR2_D',
  'SRW9',
  'MW',
  'AMW',
  'WTPT-3',
  'WPOL'],
 'plot': Figure({
     'data': [{'mode': 'markers',
               'name': 'objective_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.640092460500481, 0.6498692549743975, 0.6466306275156297,
                           0.6479235723606445, 0.6529165176279803, 0.6611595489388765,
                           0.6565843936217074, 0.6555309509156758, 0.6555309509156758,
                           0.6565843936217074, 0.6611983146029782, 0.6624144935609708,
                           0.6633507498600018, 0.6633507498600018, 0.6642722970415573,
                           0.6640680615480681, 0.6649479047503188, 0.6649479047503188,
                           0.6660167783129438, 0.6660167783129438, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369], dtype=object)},
              {'mode': 'lines+markers',
               'name': 'best_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.640092460500481, 0.6498692549743975, 0.6498692549743975,
                           0.6498692549743975, 0.6529165176279803, 0.6611595489388765,
                           0.6611595489388765, 0.6611595489388765, 0.6611595489388765,
                           0.6611595489388765, 0.6611983146029782, 0.6624144935609708,
                           0.6633507498600018, 0.6633507498600018, 0.6642722970415573,
                           0.6642722970415573, 0.6649479047503188, 0.6649479047503188,
                           0.6660167783129438, 0.6660167783129438, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369, 0.6662100136743369,
                           0.6662100136743369, 0.6662100136743369], dtype=object)}],
     'layout': {'template': '...',
                'title': {'text': 'Optimization History Plot'},
                'xaxis': {'title': {'text': 'Iteration'}},
                'yaxis': {'title': {'text': 'objective_score'}}}
 })}


solutions_rbf['best_solution']['plot']


# Define machine learning model
svr_poly_model = SVR(kernel='poly')
# Multiple run GA with those machine learning model
solutions_poly = multiple_run_fs(20, svr_poly_model, X_train, y_train, X_valid, y_valid)


 ----------------------------------------------------------------------------------------
Run Number - 1
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4906653620059632 					 0.4906653620059632 
Iteration 1 	 0.4957713678538117 					 0.4957713678538117 
Iteration 2 	 0.5034007770163956 					 0.5034007770163956 
Iteration 3 	 0.5028860098626213 					 0.5034007770163956 
Iteration 4 	 0.5024461635355647 					 0.5034007770163956 
Iteration 5 	 0.5067019608020727 					 0.5067019608020727 
Iteration 6 	 0.507551205723403 					 0.507551205723403 
Iteration 7 	 0.5067019608020727 					 0.507551205723403 
Iteration 8 	 0.5067019608020727 					 0.507551205723403 
Iteration 9 	 0.507551205723403 					 0.507551205723403 
Iteration 10 	 0.5071520904426221 					 0.507551205723403 
Iteration 11 	 0.5084790971679103 					 0.5084790971679103 
Iteration 12 	 0.507854681296768 					 0.5084790971679103 
Iteration 13 	 0.507854681296768 					 0.5084790971679103 
Iteration 14 	 0.507854681296768 					 0.5084790971679103 
Iteration 15 	 0.507854681296768 					 0.5084790971679103 
Iteration 16 	 0.507854681296768 					 0.5084790971679103 
Iteration 17 	 0.507854681296768 					 0.5084790971679103 
Iteration 18 	 0.507854681296768 					 0.5084790971679103 
Iteration 19 	 0.507854681296768 					 0.5084790971679103 
Iteration 20 	 0.507854681296768 					 0.5084790971679103 
Iteration 21 	 0.507854681296768 					 0.5084790971679103 
Iteration 22 	 0.507854681296768 					 0.5084790971679103 
Iteration 23 	 0.507854681296768 					 0.5084790971679103 
Iteration 24 	 0.507854681296768 					 0.5084790971679103 
Iteration 25 	 0.507854681296768 					 0.5084790971679103 
Iteration 26 	 0.507854681296768 					 0.5084790971679103 
Iteration 27 	 0.507854681296768 					 0.5084790971679103 
Iteration 28 	 0.507854681296768 					 0.5084790971679103 
Iteration 29 	 0.507854681296768 					 0.5084790971679103 
Iteration 30 	 0.507854681296768 					 0.5084790971679103 
Iteration 31 	 0.507854681296768 					 0.5084790971679103 
Iteration 32 	 0.507854681296768 					 0.5084790971679103 
Iteration 33 	 0.507854681296768 					 0.5084790971679103 
Iteration 34 	 0.507854681296768 					 0.5084790971679103 
Iteration 35 	 0.507854681296768 					 0.5084790971679103 
Iteration 36 	 0.507854681296768 					 0.5084790971679103 
Iteration 37 	 0.507854681296768 					 0.5084790971679103 
Iteration 38 	 0.507854681296768 					 0.5084790971679103 
Iteration 39 	 0.507854681296768 					 0.5084790971679103 
Iteration 40 	 0.507854681296768 					 0.5084790971679103 
Iteration 41 	 0.507854681296768 					 0.5084790971679103 
Iteration 42 	 0.507854681296768 					 0.5084790971679103 
Iteration 43 	 0.507854681296768 					 0.5084790971679103 
Iteration 44 	 0.507854681296768 					 0.5084790971679103 
Iteration 45 	 0.507854681296768 					 0.5084790971679103 
Iteration 46 	 0.507854681296768 					 0.5084790971679103 
Iteration 47 	 0.507854681296768 					 0.5084790971679103 
Iteration 48 	 0.507854681296768 					 0.5084790971679103 
Iteration 49 	 0.507854681296768 					 0.5084790971679103 


 ----------------------------------------------------------------------------------------
Run Number - 2
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4967939145890624 					 0.4967939145890624 
Iteration 1 	 0.5344852611762937 					 0.5344852611762937 
Iteration 2 	 0.5344852611762937 					 0.5344852611762937 
Iteration 3 	 0.5369427817438766 					 0.5369427817438766 
Iteration 4 	 0.5278219374245934 					 0.5369427817438766 
Iteration 5 	 0.5278219374245934 					 0.5369427817438766 
Iteration 6 	 0.5278219374245934 					 0.5369427817438766 
Iteration 7 	 0.5298476562886596 					 0.5369427817438766 
Iteration 8 	 0.5308622834750756 					 0.5369427817438766 
Iteration 9 	 0.5308622834750756 					 0.5369427817438766 
Iteration 10 	 0.5308622834750756 					 0.5369427817438766 
Iteration 11 	 0.5308622834750756 					 0.5369427817438766 
Iteration 12 	 0.5309511366198147 					 0.5369427817438766 
Iteration 13 	 0.5309511366198147 					 0.5369427817438766 
Iteration 14 	 0.5309511366198147 					 0.5369427817438766 
Iteration 15 	 0.5309511366198147 					 0.5369427817438766 
Iteration 16 	 0.5309511366198147 					 0.5369427817438766 
Iteration 17 	 0.5309511366198147 					 0.5369427817438766 
Iteration 18 	 0.5309511366198147 					 0.5369427817438766 
Iteration 19 	 0.5309511366198147 					 0.5369427817438766 
Iteration 20 	 0.5309511366198147 					 0.5369427817438766 
Iteration 21 	 0.5309511366198147 					 0.5369427817438766 
Iteration 22 	 0.5309511366198147 					 0.5369427817438766 
Iteration 23 	 0.5309511366198147 					 0.5369427817438766 
Iteration 24 	 0.5309511366198147 					 0.5369427817438766 
Iteration 25 	 0.5309511366198147 					 0.5369427817438766 
Iteration 26 	 0.5309511366198147 					 0.5369427817438766 
Iteration 27 	 0.5309511366198147 					 0.5369427817438766 
Iteration 28 	 0.5309511366198147 					 0.5369427817438766 
Iteration 29 	 0.5309511366198147 					 0.5369427817438766 
Iteration 30 	 0.5309511366198147 					 0.5369427817438766 
Iteration 31 	 0.5309511366198147 					 0.5369427817438766 
Iteration 32 	 0.5309511366198147 					 0.5369427817438766 
Iteration 33 	 0.5309511366198147 					 0.5369427817438766 
Iteration 34 	 0.5309511366198147 					 0.5369427817438766 
Iteration 35 	 0.5309511366198147 					 0.5369427817438766 
Iteration 36 	 0.5309511366198147 					 0.5369427817438766 
Iteration 37 	 0.5309511366198147 					 0.5369427817438766 
Iteration 38 	 0.5309511366198147 					 0.5369427817438766 
Iteration 39 	 0.5309511366198147 					 0.5369427817438766 
Iteration 40 	 0.5309511366198147 					 0.5369427817438766 
Iteration 41 	 0.5309511366198147 					 0.5369427817438766 
Iteration 42 	 0.5309511366198147 					 0.5369427817438766 
Iteration 43 	 0.5309511366198147 					 0.5369427817438766 
Iteration 44 	 0.5309511366198147 					 0.5369427817438766 
Iteration 45 	 0.5309511366198147 					 0.5369427817438766 
Iteration 46 	 0.5309511366198147 					 0.5369427817438766 
Iteration 47 	 0.5309511366198147 					 0.5369427817438766 
Iteration 48 	 0.5309511366198147 					 0.5369427817438766 
Iteration 49 	 0.5309511366198147 					 0.5369427817438766 


 ----------------------------------------------------------------------------------------
Run Number - 3
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5016905951243928 					 0.5016905951243928 
Iteration 1 	 0.5069284341203699 					 0.5069284341203699 
Iteration 2 	 0.5030089688491964 					 0.5069284341203699 
Iteration 3 	 0.5051441697895792 					 0.5069284341203699 
Iteration 4 	 0.5051441697895792 					 0.5069284341203699 
Iteration 5 	 0.5051441697895792 					 0.5069284341203699 
Iteration 6 	 0.511571285368776 					 0.511571285368776 
Iteration 7 	 0.511571285368776 					 0.511571285368776 
Iteration 8 	 0.511571285368776 					 0.511571285368776 
Iteration 9 	 0.5154062135957657 					 0.5154062135957657 
Iteration 10 	 0.5154062135957657 					 0.5154062135957657 
Iteration 11 	 0.5154062135957657 					 0.5154062135957657 
Iteration 12 	 0.5154062135957657 					 0.5154062135957657 
Iteration 13 	 0.5154062135957657 					 0.5154062135957657 
Iteration 14 	 0.5154062135957657 					 0.5154062135957657 
Iteration 15 	 0.5154062135957657 					 0.5154062135957657 
Iteration 16 	 0.5154062135957657 					 0.5154062135957657 
Iteration 17 	 0.5154062135957657 					 0.5154062135957657 
Iteration 18 	 0.5154062135957657 					 0.5154062135957657 
Iteration 19 	 0.5154062135957657 					 0.5154062135957657 
Iteration 20 	 0.5154062135957657 					 0.5154062135957657 
Iteration 21 	 0.5154062135957657 					 0.5154062135957657 
Iteration 22 	 0.5154062135957657 					 0.5154062135957657 
Iteration 23 	 0.5154062135957657 					 0.5154062135957657 
Iteration 24 	 0.5154062135957657 					 0.5154062135957657 
Iteration 25 	 0.5154062135957657 					 0.5154062135957657 
Iteration 26 	 0.5154062135957657 					 0.5154062135957657 
Iteration 27 	 0.5154062135957657 					 0.5154062135957657 
Iteration 28 	 0.5154062135957657 					 0.5154062135957657 
Iteration 29 	 0.5154062135957657 					 0.5154062135957657 
Iteration 30 	 0.5154062135957657 					 0.5154062135957657 
Iteration 31 	 0.5154062135957657 					 0.5154062135957657 
Iteration 32 	 0.5154062135957657 					 0.5154062135957657 
Iteration 33 	 0.5154062135957657 					 0.5154062135957657 
Iteration 34 	 0.5154062135957657 					 0.5154062135957657 
Iteration 35 	 0.5154062135957657 					 0.5154062135957657 
Iteration 36 	 0.5154062135957657 					 0.5154062135957657 
Iteration 37 	 0.5154062135957657 					 0.5154062135957657 
Iteration 38 	 0.5154062135957657 					 0.5154062135957657 
Iteration 39 	 0.5154062135957657 					 0.5154062135957657 
Iteration 40 	 0.5154062135957657 					 0.5154062135957657 
Iteration 41 	 0.5154062135957657 					 0.5154062135957657 
Iteration 42 	 0.5154062135957657 					 0.5154062135957657 
Iteration 43 	 0.5154062135957657 					 0.5154062135957657 
Iteration 44 	 0.5154062135957657 					 0.5154062135957657 
Iteration 45 	 0.5154062135957657 					 0.5154062135957657 
Iteration 46 	 0.5154062135957657 					 0.5154062135957657 
Iteration 47 	 0.5154062135957657 					 0.5154062135957657 
Iteration 48 	 0.5154062135957657 					 0.5154062135957657 
Iteration 49 	 0.5154062135957657 					 0.5154062135957657 


 ----------------------------------------------------------------------------------------
Run Number - 4
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5070532366725877 					 0.5070532366725877 
Iteration 1 	 0.5061556647395824 					 0.5070532366725877 
Iteration 2 	 0.5103045386186573 					 0.5103045386186573 
Iteration 3 	 0.5148179541989683 					 0.5148179541989683 
Iteration 4 	 0.5148179541989683 					 0.5148179541989683 
Iteration 5 	 0.5178448085959302 					 0.5178448085959302 
Iteration 6 	 0.5231406878974081 					 0.5231406878974081 
Iteration 7 	 0.5240044711014998 					 0.5240044711014998 
Iteration 8 	 0.5240044711014998 					 0.5240044711014998 
Iteration 9 	 0.5266658237675979 					 0.5266658237675979 
Iteration 10 	 0.5266352064391938 					 0.5266658237675979 
Iteration 11 	 0.5299131977420252 					 0.5299131977420252 
Iteration 12 	 0.5315069091219682 					 0.5315069091219682 
Iteration 13 	 0.5315069091219682 					 0.5315069091219682 
Iteration 14 	 0.5315069091219682 					 0.5315069091219682 
Iteration 15 	 0.5315069091219682 					 0.5315069091219682 
Iteration 16 	 0.5315069091219682 					 0.5315069091219682 
Iteration 17 	 0.5315069091219682 					 0.5315069091219682 
Iteration 18 	 0.5315069091219682 					 0.5315069091219682 
Iteration 19 	 0.5315069091219682 					 0.5315069091219682 
Iteration 20 	 0.5315069091219682 					 0.5315069091219682 
Iteration 21 	 0.5315069091219682 					 0.5315069091219682 
Iteration 22 	 0.5315069091219682 					 0.5315069091219682 
Iteration 23 	 0.5315069091219682 					 0.5315069091219682 
Iteration 24 	 0.5315069091219682 					 0.5315069091219682 
Iteration 25 	 0.5315069091219682 					 0.5315069091219682 
Iteration 26 	 0.5315069091219682 					 0.5315069091219682 
Iteration 27 	 0.5315069091219682 					 0.5315069091219682 
Iteration 28 	 0.5315069091219682 					 0.5315069091219682 
Iteration 29 	 0.5315069091219682 					 0.5315069091219682 
Iteration 30 	 0.5315069091219682 					 0.5315069091219682 
Iteration 31 	 0.5315069091219682 					 0.5315069091219682 
Iteration 32 	 0.5315069091219682 					 0.5315069091219682 
Iteration 33 	 0.5315069091219682 					 0.5315069091219682 
Iteration 34 	 0.5315069091219682 					 0.5315069091219682 
Iteration 35 	 0.5315069091219682 					 0.5315069091219682 
Iteration 36 	 0.5315069091219682 					 0.5315069091219682 
Iteration 37 	 0.5315069091219682 					 0.5315069091219682 
Iteration 38 	 0.5315069091219682 					 0.5315069091219682 
Iteration 39 	 0.5315069091219682 					 0.5315069091219682 
Iteration 40 	 0.5315069091219682 					 0.5315069091219682 
Iteration 41 	 0.5315069091219682 					 0.5315069091219682 
Iteration 42 	 0.5315069091219682 					 0.5315069091219682 
Iteration 43 	 0.5315069091219682 					 0.5315069091219682 
Iteration 44 	 0.5315069091219682 					 0.5315069091219682 
Iteration 45 	 0.5315069091219682 					 0.5315069091219682 
Iteration 46 	 0.5315069091219682 					 0.5315069091219682 
Iteration 47 	 0.5315069091219682 					 0.5315069091219682 
Iteration 48 	 0.5315069091219682 					 0.5315069091219682 
Iteration 49 	 0.5315069091219682 					 0.5315069091219682 


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Run Number - 5
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5042426036211191 					 0.5042426036211191 
Iteration 1 	 0.5104172189670158 					 0.5104172189670158 
Iteration 2 	 0.505694811737807 					 0.5104172189670158 
Iteration 3 	 0.514604526798359 					 0.514604526798359 
Iteration 4 	 0.5195650424111041 					 0.5195650424111041 
Iteration 5 	 0.5221533273340976 					 0.5221533273340976 
Iteration 6 	 0.5291988426638418 					 0.5291988426638418 
Iteration 7 	 0.5291988426638418 					 0.5291988426638418 
Iteration 8 	 0.5299159349912584 					 0.5299159349912584 
Iteration 9 	 0.5302922627477158 					 0.5302922627477158 
Iteration 10 	 0.5302922627477158 					 0.5302922627477158 
Iteration 11 	 0.5306757684511332 					 0.5306757684511332 
Iteration 12 	 0.5306757684511332 					 0.5306757684511332 
Iteration 13 	 0.5306757684511332 					 0.5306757684511332 
Iteration 14 	 0.5319274712089365 					 0.5319274712089365 
Iteration 15 	 0.5323473193148022 					 0.5323473193148022 
Iteration 16 	 0.5365489509443903 					 0.5365489509443903 
Iteration 17 	 0.5322114899025094 					 0.5365489509443903 
Iteration 18 	 0.5355013112712632 					 0.5365489509443903 
Iteration 19 	 0.5325768649602742 					 0.5365489509443903 
Iteration 20 	 0.5348906029530738 					 0.5365489509443903 
Iteration 21 	 0.5386171070962273 					 0.5386171070962273 
Iteration 22 	 0.5386171070962273 					 0.5386171070962273 
Iteration 23 	 0.5386862909071404 					 0.5386862909071404 
Iteration 24 	 0.5386862909071404 					 0.5386862909071404 
Iteration 25 	 0.5386862909071404 					 0.5386862909071404 
Iteration 26 	 0.5386862909071404 					 0.5386862909071404 
Iteration 27 	 0.5421591615982104 					 0.5421591615982104 
Iteration 28 	 0.5394540288693445 					 0.5421591615982104 
Iteration 29 	 0.5421591615982104 					 0.5421591615982104 
Iteration 30 	 0.5421591615982104 					 0.5421591615982104 
Iteration 31 	 0.5421591615982104 					 0.5421591615982104 
Iteration 32 	 0.5421591615982104 					 0.5421591615982104 
Iteration 33 	 0.5421591615982104 					 0.5421591615982104 
Iteration 34 	 0.5421591615982104 					 0.5421591615982104 
Iteration 35 	 0.5421591615982104 					 0.5421591615982104 
Iteration 36 	 0.5421591615982104 					 0.5421591615982104 
Iteration 37 	 0.5421591615982104 					 0.5421591615982104 
Iteration 38 	 0.5421591615982104 					 0.5421591615982104 
Iteration 39 	 0.5421591615982104 					 0.5421591615982104 
Iteration 40 	 0.5421591615982104 					 0.5421591615982104 
Iteration 41 	 0.5421591615982104 					 0.5421591615982104 
Iteration 42 	 0.5421591615982104 					 0.5421591615982104 
Iteration 43 	 0.5421591615982104 					 0.5421591615982104 
Iteration 44 	 0.5421591615982104 					 0.5421591615982104 
Iteration 45 	 0.5421591615982104 					 0.5421591615982104 
Iteration 46 	 0.5421591615982104 					 0.5421591615982104 
Iteration 47 	 0.5421591615982104 					 0.5421591615982104 
Iteration 48 	 0.5421591615982104 					 0.5421591615982104 
Iteration 49 	 0.5421591615982104 					 0.5421591615982104 


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Run Number - 6
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4999121937700125 					 0.4999121937700125 
Iteration 1 	 0.5043424620535308 					 0.5043424620535308 
Iteration 2 	 0.5074501786711196 					 0.5074501786711196 
Iteration 3 	 0.5147742237996712 					 0.5147742237996712 
Iteration 4 	 0.512632169710694 					 0.5147742237996712 
Iteration 5 	 0.5194321412112027 					 0.5194321412112027 
Iteration 6 	 0.5194321412112027 					 0.5194321412112027 
Iteration 7 	 0.5194321412112027 					 0.5194321412112027 
Iteration 8 	 0.5194321412112027 					 0.5194321412112027 
Iteration 9 	 0.5194321412112027 					 0.5194321412112027 
Iteration 10 	 0.521967885073781 					 0.521967885073781 
Iteration 11 	 0.5194321412112027 					 0.521967885073781 
Iteration 12 	 0.5209907839858965 					 0.521967885073781 
Iteration 13 	 0.5209907839858965 					 0.521967885073781 
Iteration 14 	 0.5194321412112027 					 0.521967885073781 
Iteration 15 	 0.5194321412112027 					 0.521967885073781 
Iteration 16 	 0.5194321412112027 					 0.521967885073781 
Iteration 17 	 0.5194321412112027 					 0.521967885073781 
Iteration 18 	 0.5194321412112027 					 0.521967885073781 
Iteration 19 	 0.5194321412112027 					 0.521967885073781 
Iteration 20 	 0.5194321412112027 					 0.521967885073781 
Iteration 21 	 0.5194321412112027 					 0.521967885073781 
Iteration 22 	 0.5194321412112027 					 0.521967885073781 
Iteration 23 	 0.5194321412112027 					 0.521967885073781 
Iteration 24 	 0.5194321412112027 					 0.521967885073781 
Iteration 25 	 0.5194321412112027 					 0.521967885073781 
Iteration 26 	 0.5194321412112027 					 0.521967885073781 
Iteration 27 	 0.5194321412112027 					 0.521967885073781 
Iteration 28 	 0.5194321412112027 					 0.521967885073781 
Iteration 29 	 0.5194321412112027 					 0.521967885073781 
Iteration 30 	 0.5194321412112027 					 0.521967885073781 
Iteration 31 	 0.5194321412112027 					 0.521967885073781 
Iteration 32 	 0.5194321412112027 					 0.521967885073781 
Iteration 33 	 0.5194321412112027 					 0.521967885073781 
Iteration 34 	 0.5194321412112027 					 0.521967885073781 
Iteration 35 	 0.5194321412112027 					 0.521967885073781 
Iteration 36 	 0.5194321412112027 					 0.521967885073781 
Iteration 37 	 0.5194321412112027 					 0.521967885073781 
Iteration 38 	 0.5194321412112027 					 0.521967885073781 
Iteration 39 	 0.5194321412112027 					 0.521967885073781 
Iteration 40 	 0.5194321412112027 					 0.521967885073781 
Iteration 41 	 0.5194321412112027 					 0.521967885073781 
Iteration 42 	 0.5194321412112027 					 0.521967885073781 
Iteration 43 	 0.5194321412112027 					 0.521967885073781 
Iteration 44 	 0.5194321412112027 					 0.521967885073781 
Iteration 45 	 0.5194321412112027 					 0.521967885073781 
Iteration 46 	 0.5194321412112027 					 0.521967885073781 
Iteration 47 	 0.5194321412112027 					 0.521967885073781 
Iteration 48 	 0.5194321412112027 					 0.521967885073781 
Iteration 49 	 0.5194321412112027 					 0.521967885073781 


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Run Number - 7
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5127056809848817 					 0.5127056809848817 
Iteration 1 	 0.511216261860083 					 0.5127056809848817 
Iteration 2 	 0.5144304069241662 					 0.5144304069241662 
Iteration 3 	 0.5185876445597056 					 0.5185876445597056 
Iteration 4 	 0.5291792841001473 					 0.5291792841001473 
Iteration 5 	 0.5313766430989582 					 0.5313766430989582 
Iteration 6 	 0.547749069107153 					 0.547749069107153 
Iteration 7 	 0.547749069107153 					 0.547749069107153 
Iteration 8 	 0.547749069107153 					 0.547749069107153 
Iteration 9 	 0.547749069107153 					 0.547749069107153 
Iteration 10 	 0.547749069107153 					 0.547749069107153 
Iteration 11 	 0.547749069107153 					 0.547749069107153 
Iteration 12 	 0.547749069107153 					 0.547749069107153 
Iteration 13 	 0.547749069107153 					 0.547749069107153 
Iteration 14 	 0.547749069107153 					 0.547749069107153 
Iteration 15 	 0.5478640411062131 					 0.5478640411062131 
Iteration 16 	 0.5478640411062131 					 0.5478640411062131 
Iteration 17 	 0.5478640411062131 					 0.5478640411062131 
Iteration 18 	 0.5478640411062131 					 0.5478640411062131 
Iteration 19 	 0.5478640411062131 					 0.5478640411062131 
Iteration 20 	 0.5478640411062131 					 0.5478640411062131 
Iteration 21 	 0.5478640411062131 					 0.5478640411062131 
Iteration 22 	 0.5478640411062131 					 0.5478640411062131 
Iteration 23 	 0.5478640411062131 					 0.5478640411062131 
Iteration 24 	 0.5478640411062131 					 0.5478640411062131 
Iteration 25 	 0.5478640411062131 					 0.5478640411062131 
Iteration 26 	 0.5478640411062131 					 0.5478640411062131 
Iteration 27 	 0.5478640411062131 					 0.5478640411062131 
Iteration 28 	 0.5478640411062131 					 0.5478640411062131 
Iteration 29 	 0.5478640411062131 					 0.5478640411062131 
Iteration 30 	 0.5478640411062131 					 0.5478640411062131 
Iteration 31 	 0.5478640411062131 					 0.5478640411062131 
Iteration 32 	 0.5478640411062131 					 0.5478640411062131 
Iteration 33 	 0.5478640411062131 					 0.5478640411062131 
Iteration 34 	 0.5478640411062131 					 0.5478640411062131 
Iteration 35 	 0.5478640411062131 					 0.5478640411062131 
Iteration 36 	 0.5478640411062131 					 0.5478640411062131 
Iteration 37 	 0.5478640411062131 					 0.5478640411062131 
Iteration 38 	 0.5478640411062131 					 0.5478640411062131 
Iteration 39 	 0.5478640411062131 					 0.5478640411062131 
Iteration 40 	 0.5478640411062131 					 0.5478640411062131 
Iteration 41 	 0.5478640411062131 					 0.5478640411062131 
Iteration 42 	 0.5478640411062131 					 0.5478640411062131 
Iteration 43 	 0.5478640411062131 					 0.5478640411062131 
Iteration 44 	 0.5478640411062131 					 0.5478640411062131 
Iteration 45 	 0.5478640411062131 					 0.5478640411062131 
Iteration 46 	 0.5478640411062131 					 0.5478640411062131 
Iteration 47 	 0.5478640411062131 					 0.5478640411062131 
Iteration 48 	 0.5478640411062131 					 0.5478640411062131 
Iteration 49 	 0.5478640411062131 					 0.5478640411062131 


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Run Number - 8
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5075635802996257 					 0.5075635802996257 
Iteration 1 	 0.49642570972003275 					 0.5075635802996257 
Iteration 2 	 0.5004195889977152 					 0.5075635802996257 
Iteration 3 	 0.49665014487989634 					 0.5075635802996257 
Iteration 4 	 0.502992910574727 					 0.5075635802996257 
Iteration 5 	 0.502992910574727 					 0.5075635802996257 
Iteration 6 	 0.5038476270173845 					 0.5075635802996257 
Iteration 7 	 0.516401612873734 					 0.516401612873734 
Iteration 8 	 0.5145289986669817 					 0.516401612873734 
Iteration 9 	 0.5140474671449147 					 0.516401612873734 
Iteration 10 	 0.5156652102509656 					 0.516401612873734 
Iteration 11 	 0.5174475817957565 					 0.5174475817957565 
Iteration 12 	 0.5171407157119715 					 0.5174475817957565 
Iteration 13 	 0.5174475817957565 					 0.5174475817957565 
Iteration 14 	 0.5171407157119715 					 0.5174475817957565 
Iteration 15 	 0.5171407157119715 					 0.5174475817957565 
Iteration 16 	 0.5171407157119715 					 0.5174475817957565 
Iteration 17 	 0.5171407157119715 					 0.5174475817957565 
Iteration 18 	 0.5171407157119715 					 0.5174475817957565 
Iteration 19 	 0.5171407157119715 					 0.5174475817957565 
Iteration 20 	 0.5171407157119715 					 0.5174475817957565 
Iteration 21 	 0.5171407157119715 					 0.5174475817957565 
Iteration 22 	 0.5171407157119715 					 0.5174475817957565 
Iteration 23 	 0.5171407157119715 					 0.5174475817957565 
Iteration 24 	 0.5171407157119715 					 0.5174475817957565 
Iteration 25 	 0.5171407157119715 					 0.5174475817957565 
Iteration 26 	 0.5171407157119715 					 0.5174475817957565 
Iteration 27 	 0.5171407157119715 					 0.5174475817957565 
Iteration 28 	 0.5171407157119715 					 0.5174475817957565 
Iteration 29 	 0.5171407157119715 					 0.5174475817957565 
Iteration 30 	 0.5171407157119715 					 0.5174475817957565 
Iteration 31 	 0.5171407157119715 					 0.5174475817957565 
Iteration 32 	 0.5171407157119715 					 0.5174475817957565 
Iteration 33 	 0.5171407157119715 					 0.5174475817957565 
Iteration 34 	 0.5171407157119715 					 0.5174475817957565 
Iteration 35 	 0.5171407157119715 					 0.5174475817957565 
Iteration 36 	 0.5171407157119715 					 0.5174475817957565 
Iteration 37 	 0.5171407157119715 					 0.5174475817957565 
Iteration 38 	 0.5171407157119715 					 0.5174475817957565 
Iteration 39 	 0.5171407157119715 					 0.5174475817957565 
Iteration 40 	 0.5171407157119715 					 0.5174475817957565 
Iteration 41 	 0.5171407157119715 					 0.5174475817957565 
Iteration 42 	 0.5171407157119715 					 0.5174475817957565 
Iteration 43 	 0.5171407157119715 					 0.5174475817957565 
Iteration 44 	 0.5171407157119715 					 0.5174475817957565 
Iteration 45 	 0.5171407157119715 					 0.5174475817957565 
Iteration 46 	 0.5171407157119715 					 0.5174475817957565 
Iteration 47 	 0.5171407157119715 					 0.5174475817957565 
Iteration 48 	 0.5171407157119715 					 0.5174475817957565 
Iteration 49 	 0.5171407157119715 					 0.5174475817957565 


 ----------------------------------------------------------------------------------------
Run Number - 9
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4963016787277686 					 0.4963016787277686 
Iteration 1 	 0.48905457274435965 					 0.4963016787277686 
Iteration 2 	 0.49414355169542856 					 0.4963016787277686 
Iteration 3 	 0.4946003323859116 					 0.4963016787277686 
Iteration 4 	 0.4982217266553657 					 0.4982217266553657 
Iteration 5 	 0.5014622535633771 					 0.5014622535633771 
Iteration 6 	 0.5105940254366641 					 0.5105940254366641 
Iteration 7 	 0.5114522702692315 					 0.5114522702692315 
Iteration 8 	 0.5117073439948622 					 0.5117073439948622 
Iteration 9 	 0.514866266339651 					 0.514866266339651 
Iteration 10 	 0.5195841053671151 					 0.5195841053671151 
Iteration 11 	 0.5214615858717369 					 0.5214615858717369 
Iteration 12 	 0.5251795139819962 					 0.5251795139819962 
Iteration 13 	 0.5251795139819962 					 0.5251795139819962 
Iteration 14 	 0.5231553440450245 					 0.5251795139819962 
Iteration 15 	 0.5231553440450245 					 0.5251795139819962 
Iteration 16 	 0.5253952089829755 					 0.5253952089829755 
Iteration 17 	 0.5253952089829755 					 0.5253952089829755 
Iteration 18 	 0.5253952089829755 					 0.5253952089829755 
Iteration 19 	 0.5253952089829755 					 0.5253952089829755 
Iteration 20 	 0.5253952089829755 					 0.5253952089829755 
Iteration 21 	 0.5253952089829755 					 0.5253952089829755 
Iteration 22 	 0.5253952089829755 					 0.5253952089829755 
Iteration 23 	 0.5253952089829755 					 0.5253952089829755 
Iteration 24 	 0.5253952089829755 					 0.5253952089829755 
Iteration 25 	 0.5253952089829755 					 0.5253952089829755 
Iteration 26 	 0.5253952089829755 					 0.5253952089829755 
Iteration 27 	 0.5253952089829755 					 0.5253952089829755 
Iteration 28 	 0.5253952089829755 					 0.5253952089829755 
Iteration 29 	 0.5253952089829755 					 0.5253952089829755 
Iteration 30 	 0.5253952089829755 					 0.5253952089829755 
Iteration 31 	 0.5253952089829755 					 0.5253952089829755 
Iteration 32 	 0.5253952089829755 					 0.5253952089829755 
Iteration 33 	 0.5253952089829755 					 0.5253952089829755 
Iteration 34 	 0.5253952089829755 					 0.5253952089829755 
Iteration 35 	 0.5253952089829755 					 0.5253952089829755 
Iteration 36 	 0.5253952089829755 					 0.5253952089829755 
Iteration 37 	 0.5253952089829755 					 0.5253952089829755 
Iteration 38 	 0.5253952089829755 					 0.5253952089829755 
Iteration 39 	 0.5253952089829755 					 0.5253952089829755 
Iteration 40 	 0.5253952089829755 					 0.5253952089829755 
Iteration 41 	 0.5253952089829755 					 0.5253952089829755 
Iteration 42 	 0.5253952089829755 					 0.5253952089829755 
Iteration 43 	 0.5253952089829755 					 0.5253952089829755 
Iteration 44 	 0.5253952089829755 					 0.5253952089829755 
Iteration 45 	 0.5253952089829755 					 0.5253952089829755 
Iteration 46 	 0.5253952089829755 					 0.5253952089829755 
Iteration 47 	 0.5253952089829755 					 0.5253952089829755 
Iteration 48 	 0.5253952089829755 					 0.5253952089829755 
Iteration 49 	 0.5253952089829755 					 0.5253952089829755 


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Run Number - 10
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5058456330904416 					 0.5058456330904416 
Iteration 1 	 0.5044220470849874 					 0.5058456330904416 
Iteration 2 	 0.5107678308046041 					 0.5107678308046041 
Iteration 3 	 0.5091744964591356 					 0.5107678308046041 
Iteration 4 	 0.5091456335546158 					 0.5107678308046041 
Iteration 5 	 0.5109810051502186 					 0.5109810051502186 
Iteration 6 	 0.5109389515185463 					 0.5109810051502186 
Iteration 7 	 0.5133418625729363 					 0.5133418625729363 
Iteration 8 	 0.5145706939172454 					 0.5145706939172454 
Iteration 9 	 0.517517554053221 					 0.517517554053221 
Iteration 10 	 0.517117224852252 					 0.517517554053221 
Iteration 11 	 0.5162645096317315 					 0.517517554053221 
Iteration 12 	 0.518017616894496 					 0.518017616894496 
Iteration 13 	 0.5194609610166053 					 0.5194609610166053 
Iteration 14 	 0.5199813454033955 					 0.5199813454033955 
Iteration 15 	 0.5225387206727808 					 0.5225387206727808 
Iteration 16 	 0.5225387206727808 					 0.5225387206727808 
Iteration 17 	 0.5225387206727808 					 0.5225387206727808 
Iteration 18 	 0.5225387206727808 					 0.5225387206727808 
Iteration 19 	 0.5225387206727808 					 0.5225387206727808 
Iteration 20 	 0.5225387206727808 					 0.5225387206727808 
Iteration 21 	 0.5225387206727808 					 0.5225387206727808 
Iteration 22 	 0.5225387206727808 					 0.5225387206727808 
Iteration 23 	 0.5225387206727808 					 0.5225387206727808 
Iteration 24 	 0.5225387206727808 					 0.5225387206727808 
Iteration 25 	 0.5225387206727808 					 0.5225387206727808 
Iteration 26 	 0.5225387206727808 					 0.5225387206727808 
Iteration 27 	 0.5225387206727808 					 0.5225387206727808 
Iteration 28 	 0.5225387206727808 					 0.5225387206727808 
Iteration 29 	 0.5225387206727808 					 0.5225387206727808 
Iteration 30 	 0.5225387206727808 					 0.5225387206727808 
Iteration 31 	 0.5225387206727808 					 0.5225387206727808 
Iteration 32 	 0.5225387206727808 					 0.5225387206727808 
Iteration 33 	 0.5225387206727808 					 0.5225387206727808 
Iteration 34 	 0.5225387206727808 					 0.5225387206727808 
Iteration 35 	 0.5225387206727808 					 0.5225387206727808 
Iteration 36 	 0.5225387206727808 					 0.5225387206727808 
Iteration 37 	 0.5225387206727808 					 0.5225387206727808 
Iteration 38 	 0.5225387206727808 					 0.5225387206727808 
Iteration 39 	 0.5225387206727808 					 0.5225387206727808 
Iteration 40 	 0.5225387206727808 					 0.5225387206727808 
Iteration 41 	 0.5225387206727808 					 0.5225387206727808 
Iteration 42 	 0.5225387206727808 					 0.5225387206727808 
Iteration 43 	 0.5225387206727808 					 0.5225387206727808 
Iteration 44 	 0.5225387206727808 					 0.5225387206727808 
Iteration 45 	 0.5225387206727808 					 0.5225387206727808 
Iteration 46 	 0.5225387206727808 					 0.5225387206727808 
Iteration 47 	 0.5225387206727808 					 0.5225387206727808 
Iteration 48 	 0.5225387206727808 					 0.5225387206727808 
Iteration 49 	 0.5225387206727808 					 0.5225387206727808 


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Run Number - 11
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5183373676616821 					 0.5183373676616821 
Iteration 1 	 0.5176906243919752 					 0.5183373676616821 
Iteration 2 	 0.5154809771447896 					 0.5183373676616821 
Iteration 3 	 0.5154283383396343 					 0.5183373676616821 
Iteration 4 	 0.5199478398073492 					 0.5199478398073492 
Iteration 5 	 0.5236116329354297 					 0.5236116329354297 
Iteration 6 	 0.5279658889369278 					 0.5279658889369278 
Iteration 7 	 0.534239849852846 					 0.534239849852846 
Iteration 8 	 0.5332591897503505 					 0.534239849852846 
Iteration 9 	 0.5281344487121075 					 0.534239849852846 
Iteration 10 	 0.5281429968447663 					 0.534239849852846 
Iteration 11 	 0.5281429968447663 					 0.534239849852846 
Iteration 12 	 0.5281429968447663 					 0.534239849852846 
Iteration 13 	 0.5281429968447663 					 0.534239849852846 
Iteration 14 	 0.5281429968447663 					 0.534239849852846 
Iteration 15 	 0.5281429968447663 					 0.534239849852846 
Iteration 16 	 0.5281429968447663 					 0.534239849852846 
Iteration 17 	 0.5281429968447663 					 0.534239849852846 
Iteration 18 	 0.5281429968447663 					 0.534239849852846 
Iteration 19 	 0.5281429968447663 					 0.534239849852846 
Iteration 20 	 0.5281429968447663 					 0.534239849852846 
Iteration 21 	 0.5281429968447663 					 0.534239849852846 
Iteration 22 	 0.5281429968447663 					 0.534239849852846 
Iteration 23 	 0.5281429968447663 					 0.534239849852846 
Iteration 24 	 0.5281429968447663 					 0.534239849852846 
Iteration 25 	 0.5281429968447663 					 0.534239849852846 
Iteration 26 	 0.5281429968447663 					 0.534239849852846 
Iteration 27 	 0.5281429968447663 					 0.534239849852846 
Iteration 28 	 0.5281429968447663 					 0.534239849852846 
Iteration 29 	 0.5281429968447663 					 0.534239849852846 
Iteration 30 	 0.5281429968447663 					 0.534239849852846 
Iteration 31 	 0.5281429968447663 					 0.534239849852846 
Iteration 32 	 0.5281429968447663 					 0.534239849852846 
Iteration 33 	 0.5281429968447663 					 0.534239849852846 
Iteration 34 	 0.5281429968447663 					 0.534239849852846 
Iteration 35 	 0.5281429968447663 					 0.534239849852846 
Iteration 36 	 0.5281429968447663 					 0.534239849852846 
Iteration 37 	 0.5281429968447663 					 0.534239849852846 
Iteration 38 	 0.5281429968447663 					 0.534239849852846 
Iteration 39 	 0.5281429968447663 					 0.534239849852846 
Iteration 40 	 0.5281429968447663 					 0.534239849852846 
Iteration 41 	 0.5281429968447663 					 0.534239849852846 
Iteration 42 	 0.5281429968447663 					 0.534239849852846 
Iteration 43 	 0.5281429968447663 					 0.534239849852846 
Iteration 44 	 0.5281429968447663 					 0.534239849852846 
Iteration 45 	 0.5281429968447663 					 0.534239849852846 
Iteration 46 	 0.5281429968447663 					 0.534239849852846 
Iteration 47 	 0.5281429968447663 					 0.534239849852846 
Iteration 48 	 0.5281429968447663 					 0.534239849852846 
Iteration 49 	 0.5281429968447663 					 0.534239849852846 


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Run Number - 12
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4972418276514776 					 0.4972418276514776 
Iteration 1 	 0.5038104658402623 					 0.5038104658402623 
Iteration 2 	 0.5046317361794489 					 0.5046317361794489 
Iteration 3 	 0.5015800896541823 					 0.5046317361794489 
Iteration 4 	 0.5009102803934785 					 0.5046317361794489 
Iteration 5 	 0.5040193570663333 					 0.5046317361794489 
Iteration 6 	 0.5096552558769727 					 0.5096552558769727 
Iteration 7 	 0.5153888749478553 					 0.5153888749478553 
Iteration 8 	 0.5153888749478553 					 0.5153888749478553 
Iteration 9 	 0.51626381104634 					 0.51626381104634 
Iteration 10 	 0.5176345977363039 					 0.5176345977363039 
Iteration 11 	 0.51820803958541 					 0.51820803958541 
Iteration 12 	 0.5187910599197791 					 0.5187910599197791 
Iteration 13 	 0.519837090173146 					 0.519837090173146 
Iteration 14 	 0.5194624605791047 					 0.519837090173146 
Iteration 15 	 0.520174761636064 					 0.520174761636064 
Iteration 16 	 0.5199937592638229 					 0.520174761636064 
Iteration 17 	 0.5211130296961365 					 0.5211130296961365 
Iteration 18 	 0.5199937592638229 					 0.5211130296961365 
Iteration 19 	 0.5199937592638229 					 0.5211130296961365 
Iteration 20 	 0.5199937592638229 					 0.5211130296961365 
Iteration 21 	 0.5199937592638229 					 0.5211130296961365 
Iteration 22 	 0.5199937592638229 					 0.5211130296961365 
Iteration 23 	 0.5199937592638229 					 0.5211130296961365 
Iteration 24 	 0.5199937592638229 					 0.5211130296961365 
Iteration 25 	 0.5199937592638229 					 0.5211130296961365 
Iteration 26 	 0.5199937592638229 					 0.5211130296961365 
Iteration 27 	 0.5199937592638229 					 0.5211130296961365 
Iteration 28 	 0.5199937592638229 					 0.5211130296961365 
Iteration 29 	 0.5199937592638229 					 0.5211130296961365 
Iteration 30 	 0.5199937592638229 					 0.5211130296961365 
Iteration 31 	 0.5199937592638229 					 0.5211130296961365 
Iteration 32 	 0.5199937592638229 					 0.5211130296961365 
Iteration 33 	 0.5199937592638229 					 0.5211130296961365 
Iteration 34 	 0.5199937592638229 					 0.5211130296961365 
Iteration 35 	 0.5199937592638229 					 0.5211130296961365 
Iteration 36 	 0.5199937592638229 					 0.5211130296961365 
Iteration 37 	 0.5199937592638229 					 0.5211130296961365 
Iteration 38 	 0.5199937592638229 					 0.5211130296961365 
Iteration 39 	 0.5199937592638229 					 0.5211130296961365 
Iteration 40 	 0.5199937592638229 					 0.5211130296961365 
Iteration 41 	 0.5199937592638229 					 0.5211130296961365 
Iteration 42 	 0.5199937592638229 					 0.5211130296961365 
Iteration 43 	 0.5199937592638229 					 0.5211130296961365 
Iteration 44 	 0.5199937592638229 					 0.5211130296961365 
Iteration 45 	 0.5199937592638229 					 0.5211130296961365 
Iteration 46 	 0.5199937592638229 					 0.5211130296961365 
Iteration 47 	 0.5199937592638229 					 0.5211130296961365 
Iteration 48 	 0.5199937592638229 					 0.5211130296961365 
Iteration 49 	 0.5199937592638229 					 0.5211130296961365 


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Run Number - 13
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4943153727022188 					 0.4943153727022188 
Iteration 1 	 0.508388398269951 					 0.508388398269951 
Iteration 2 	 0.5187134441972683 					 0.5187134441972683 
Iteration 3 	 0.5163739092996055 					 0.5187134441972683 
Iteration 4 	 0.5163739092996055 					 0.5187134441972683 
Iteration 5 	 0.5047780099507541 					 0.5187134441972683 
Iteration 6 	 0.5047780099507541 					 0.5187134441972683 
Iteration 7 	 0.5100453881738495 					 0.5187134441972683 
Iteration 8 	 0.5139850996341989 					 0.5187134441972683 
Iteration 9 	 0.5201295352161578 					 0.5201295352161578 
Iteration 10 	 0.5346512588422857 					 0.5346512588422857 
Iteration 11 	 0.530462448770509 					 0.5346512588422857 
Iteration 12 	 0.5346028018545137 					 0.5346512588422857 
Iteration 13 	 0.5346028018545137 					 0.5346512588422857 
Iteration 14 	 0.5382362608479522 					 0.5382362608479522 
Iteration 15 	 0.5382362608479522 					 0.5382362608479522 
Iteration 16 	 0.5432943159211261 					 0.5432943159211261 
Iteration 17 	 0.5432943159211261 					 0.5432943159211261 
Iteration 18 	 0.5432943159211261 					 0.5432943159211261 
Iteration 19 	 0.5432943159211261 					 0.5432943159211261 
Iteration 20 	 0.5432943159211261 					 0.5432943159211261 
Iteration 21 	 0.5459047125326714 					 0.5459047125326714 
Iteration 22 	 0.5459047125326714 					 0.5459047125326714 
Iteration 23 	 0.5459047125326714 					 0.5459047125326714 
Iteration 24 	 0.5459047125326714 					 0.5459047125326714 
Iteration 25 	 0.5459047125326714 					 0.5459047125326714 
Iteration 26 	 0.5459047125326714 					 0.5459047125326714 
Iteration 27 	 0.5459047125326714 					 0.5459047125326714 
Iteration 28 	 0.5459047125326714 					 0.5459047125326714 
Iteration 29 	 0.5459047125326714 					 0.5459047125326714 
Iteration 30 	 0.5459047125326714 					 0.5459047125326714 
Iteration 31 	 0.5459047125326714 					 0.5459047125326714 
Iteration 32 	 0.5459047125326714 					 0.5459047125326714 
Iteration 33 	 0.5459047125326714 					 0.5459047125326714 
Iteration 34 	 0.5459047125326714 					 0.5459047125326714 
Iteration 35 	 0.5459047125326714 					 0.5459047125326714 
Iteration 36 	 0.5459047125326714 					 0.5459047125326714 
Iteration 37 	 0.5459047125326714 					 0.5459047125326714 
Iteration 38 	 0.5459047125326714 					 0.5459047125326714 
Iteration 39 	 0.5459047125326714 					 0.5459047125326714 
Iteration 40 	 0.5459047125326714 					 0.5459047125326714 
Iteration 41 	 0.5459047125326714 					 0.5459047125326714 
Iteration 42 	 0.5459047125326714 					 0.5459047125326714 
Iteration 43 	 0.5459047125326714 					 0.5459047125326714 
Iteration 44 	 0.5459047125326714 					 0.5459047125326714 
Iteration 45 	 0.5459047125326714 					 0.5459047125326714 
Iteration 46 	 0.5459047125326714 					 0.5459047125326714 
Iteration 47 	 0.5459047125326714 					 0.5459047125326714 
Iteration 48 	 0.5459047125326714 					 0.5459047125326714 
Iteration 49 	 0.5459047125326714 					 0.5459047125326714 


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Run Number - 14
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.49912092667592795 					 0.49912092667592795 
Iteration 1 	 0.499621983371521 					 0.499621983371521 
Iteration 2 	 0.5039727236255216 					 0.5039727236255216 
Iteration 3 	 0.5140458478094558 					 0.5140458478094558 
Iteration 4 	 0.5140458478094558 					 0.5140458478094558 
Iteration 5 	 0.5286484801248816 					 0.5286484801248816 
Iteration 6 	 0.5260681092494107 					 0.5286484801248816 
Iteration 7 	 0.5260681092494107 					 0.5286484801248816 
Iteration 8 	 0.5323444703689115 					 0.5323444703689115 
Iteration 9 	 0.5282395058671383 					 0.5323444703689115 
Iteration 10 	 0.5300867928447356 					 0.5323444703689115 
Iteration 11 	 0.5300867928447356 					 0.5323444703689115 
Iteration 12 	 0.5300867928447356 					 0.5323444703689115 
Iteration 13 	 0.5300867928447356 					 0.5323444703689115 
Iteration 14 	 0.5313416460797191 					 0.5323444703689115 
Iteration 15 	 0.5313416460797191 					 0.5323444703689115 
Iteration 16 	 0.5313416460797191 					 0.5323444703689115 
Iteration 17 	 0.5313416460797191 					 0.5323444703689115 
Iteration 18 	 0.5313416460797191 					 0.5323444703689115 
Iteration 19 	 0.5313416460797191 					 0.5323444703689115 
Iteration 20 	 0.5313416460797191 					 0.5323444703689115 
Iteration 21 	 0.5313416460797191 					 0.5323444703689115 
Iteration 22 	 0.5313416460797191 					 0.5323444703689115 
Iteration 23 	 0.5313416460797191 					 0.5323444703689115 
Iteration 24 	 0.5313416460797191 					 0.5323444703689115 
Iteration 25 	 0.5313416460797191 					 0.5323444703689115 
Iteration 26 	 0.5313416460797191 					 0.5323444703689115 
Iteration 27 	 0.5313416460797191 					 0.5323444703689115 
Iteration 28 	 0.5313416460797191 					 0.5323444703689115 
Iteration 29 	 0.5313416460797191 					 0.5323444703689115 
Iteration 30 	 0.5313416460797191 					 0.5323444703689115 
Iteration 31 	 0.5313416460797191 					 0.5323444703689115 
Iteration 32 	 0.5313416460797191 					 0.5323444703689115 
Iteration 33 	 0.5313416460797191 					 0.5323444703689115 
Iteration 34 	 0.5313416460797191 					 0.5323444703689115 
Iteration 35 	 0.5313416460797191 					 0.5323444703689115 
Iteration 36 	 0.5313416460797191 					 0.5323444703689115 
Iteration 37 	 0.5313416460797191 					 0.5323444703689115 
Iteration 38 	 0.5313416460797191 					 0.5323444703689115 
Iteration 39 	 0.5313416460797191 					 0.5323444703689115 
Iteration 40 	 0.5313416460797191 					 0.5323444703689115 
Iteration 41 	 0.5313416460797191 					 0.5323444703689115 
Iteration 42 	 0.5313416460797191 					 0.5323444703689115 
Iteration 43 	 0.5313416460797191 					 0.5323444703689115 
Iteration 44 	 0.5313416460797191 					 0.5323444703689115 
Iteration 45 	 0.5313416460797191 					 0.5323444703689115 
Iteration 46 	 0.5313416460797191 					 0.5323444703689115 
Iteration 47 	 0.5313416460797191 					 0.5323444703689115 
Iteration 48 	 0.5313416460797191 					 0.5323444703689115 
Iteration 49 	 0.5313416460797191 					 0.5323444703689115 


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Run Number - 15
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.49850163419549054 					 0.49850163419549054 
Iteration 1 	 0.5163105996530684 					 0.5163105996530684 
Iteration 2 	 0.5182474552301921 					 0.5182474552301921 
Iteration 3 	 0.516300028366283 					 0.5182474552301921 
Iteration 4 	 0.5171938569505459 					 0.5182474552301921 
Iteration 5 	 0.5255174588329775 					 0.5255174588329775 
Iteration 6 	 0.524608225770256 					 0.5255174588329775 
Iteration 7 	 0.5385682879651565 					 0.5385682879651565 
Iteration 8 	 0.539160273065449 					 0.539160273065449 
Iteration 9 	 0.5399487273413786 					 0.5399487273413786 
Iteration 10 	 0.5399487273413786 					 0.5399487273413786 
Iteration 11 	 0.5224924421998179 					 0.5399487273413786 
Iteration 12 	 0.5224924421998179 					 0.5399487273413786 
Iteration 13 	 0.5224924421998179 					 0.5399487273413786 
Iteration 14 	 0.5224924421998179 					 0.5399487273413786 
Iteration 15 	 0.5224924421998179 					 0.5399487273413786 
Iteration 16 	 0.5224924421998179 					 0.5399487273413786 
Iteration 17 	 0.5224924421998179 					 0.5399487273413786 
Iteration 18 	 0.5224924421998179 					 0.5399487273413786 
Iteration 19 	 0.5224924421998179 					 0.5399487273413786 
Iteration 20 	 0.5224924421998179 					 0.5399487273413786 
Iteration 21 	 0.5224924421998179 					 0.5399487273413786 
Iteration 22 	 0.5224924421998179 					 0.5399487273413786 
Iteration 23 	 0.5224924421998179 					 0.5399487273413786 
Iteration 24 	 0.5224924421998179 					 0.5399487273413786 
Iteration 25 	 0.5224924421998179 					 0.5399487273413786 
Iteration 26 	 0.5224924421998179 					 0.5399487273413786 
Iteration 27 	 0.5224924421998179 					 0.5399487273413786 
Iteration 28 	 0.5224924421998179 					 0.5399487273413786 
Iteration 29 	 0.5224924421998179 					 0.5399487273413786 
Iteration 30 	 0.5224924421998179 					 0.5399487273413786 
Iteration 31 	 0.5224924421998179 					 0.5399487273413786 
Iteration 32 	 0.5224924421998179 					 0.5399487273413786 
Iteration 33 	 0.5224924421998179 					 0.5399487273413786 
Iteration 34 	 0.5224924421998179 					 0.5399487273413786 
Iteration 35 	 0.5224924421998179 					 0.5399487273413786 
Iteration 36 	 0.5224924421998179 					 0.5399487273413786 
Iteration 37 	 0.5224924421998179 					 0.5399487273413786 
Iteration 38 	 0.5224924421998179 					 0.5399487273413786 
Iteration 39 	 0.5224924421998179 					 0.5399487273413786 
Iteration 40 	 0.5224924421998179 					 0.5399487273413786 
Iteration 41 	 0.5224924421998179 					 0.5399487273413786 
Iteration 42 	 0.5224924421998179 					 0.5399487273413786 
Iteration 43 	 0.5224924421998179 					 0.5399487273413786 
Iteration 44 	 0.5224924421998179 					 0.5399487273413786 
Iteration 45 	 0.5224924421998179 					 0.5399487273413786 
Iteration 46 	 0.5224924421998179 					 0.5399487273413786 
Iteration 47 	 0.5224924421998179 					 0.5399487273413786 
Iteration 48 	 0.5224924421998179 					 0.5399487273413786 
Iteration 49 	 0.5224924421998179 					 0.5399487273413786 


 ----------------------------------------------------------------------------------------
Run Number - 16
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4921897578809681 					 0.4921897578809681 
Iteration 1 	 0.5046183575695294 					 0.5046183575695294 
Iteration 2 	 0.5245687195786445 					 0.5245687195786445 
Iteration 3 	 0.5078830662250889 					 0.5245687195786445 
Iteration 4 	 0.5151128736819144 					 0.5245687195786445 
Iteration 5 	 0.5151128736819144 					 0.5245687195786445 
Iteration 6 	 0.5202399901706735 					 0.5245687195786445 
Iteration 7 	 0.5226622957672485 					 0.5245687195786445 
Iteration 8 	 0.5259879777626377 					 0.5259879777626377 
Iteration 9 	 0.5361661324110499 					 0.5361661324110499 
Iteration 10 	 0.5361661324110499 					 0.5361661324110499 
Iteration 11 	 0.5363764686247274 					 0.5363764686247274 
Iteration 12 	 0.5361661324110499 					 0.5363764686247274 
Iteration 13 	 0.5475358411479372 					 0.5475358411479372 
Iteration 14 	 0.5387252345159556 					 0.5475358411479372 
Iteration 15 	 0.5387252345159556 					 0.5475358411479372 
Iteration 16 	 0.5387252345159556 					 0.5475358411479372 
Iteration 17 	 0.5387252345159556 					 0.5475358411479372 
Iteration 18 	 0.5387252345159556 					 0.5475358411479372 
Iteration 19 	 0.5387252345159556 					 0.5475358411479372 
Iteration 20 	 0.5387252345159556 					 0.5475358411479372 
Iteration 21 	 0.5387252345159556 					 0.5475358411479372 
Iteration 22 	 0.5387252345159556 					 0.5475358411479372 
Iteration 23 	 0.5387252345159556 					 0.5475358411479372 
Iteration 24 	 0.5387252345159556 					 0.5475358411479372 
Iteration 25 	 0.5387252345159556 					 0.5475358411479372 
Iteration 26 	 0.5387252345159556 					 0.5475358411479372 
Iteration 27 	 0.5387252345159556 					 0.5475358411479372 
Iteration 28 	 0.5387252345159556 					 0.5475358411479372 
Iteration 29 	 0.5387252345159556 					 0.5475358411479372 
Iteration 30 	 0.5387252345159556 					 0.5475358411479372 
Iteration 31 	 0.5387252345159556 					 0.5475358411479372 
Iteration 32 	 0.5387252345159556 					 0.5475358411479372 
Iteration 33 	 0.5387252345159556 					 0.5475358411479372 
Iteration 34 	 0.5387252345159556 					 0.5475358411479372 
Iteration 35 	 0.5387252345159556 					 0.5475358411479372 
Iteration 36 	 0.5387252345159556 					 0.5475358411479372 
Iteration 37 	 0.5387252345159556 					 0.5475358411479372 
Iteration 38 	 0.5387252345159556 					 0.5475358411479372 
Iteration 39 	 0.5387252345159556 					 0.5475358411479372 
Iteration 40 	 0.5387252345159556 					 0.5475358411479372 
Iteration 41 	 0.5387252345159556 					 0.5475358411479372 
Iteration 42 	 0.5387252345159556 					 0.5475358411479372 
Iteration 43 	 0.5387252345159556 					 0.5475358411479372 
Iteration 44 	 0.5387252345159556 					 0.5475358411479372 
Iteration 45 	 0.5387252345159556 					 0.5475358411479372 
Iteration 46 	 0.5387252345159556 					 0.5475358411479372 
Iteration 47 	 0.5387252345159556 					 0.5475358411479372 
Iteration 48 	 0.5387252345159556 					 0.5475358411479372 
Iteration 49 	 0.5387252345159556 					 0.5475358411479372 


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Run Number - 17
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.499024807410685 					 0.499024807410685 
Iteration 1 	 0.5025776112154305 					 0.5025776112154305 
Iteration 2 	 0.5089083547143373 					 0.5089083547143373 
Iteration 3 	 0.5087394496237923 					 0.5089083547143373 
Iteration 4 	 0.5110178480218145 					 0.5110178480218145 
Iteration 5 	 0.510008796405016 					 0.5110178480218145 
Iteration 6 	 0.5110178480218145 					 0.5110178480218145 
Iteration 7 	 0.5135556062534067 					 0.5135556062534067 
Iteration 8 	 0.5148027998644507 					 0.5148027998644507 
Iteration 9 	 0.5148027998644507 					 0.5148027998644507 
Iteration 10 	 0.5165784322769629 					 0.5165784322769629 
Iteration 11 	 0.5179727294524038 					 0.5179727294524038 
Iteration 12 	 0.5185358901764789 					 0.5185358901764789 
Iteration 13 	 0.5185358901764789 					 0.5185358901764789 
Iteration 14 	 0.5185358901764789 					 0.5185358901764789 
Iteration 15 	 0.5185358901764789 					 0.5185358901764789 
Iteration 16 	 0.5185358901764789 					 0.5185358901764789 
Iteration 17 	 0.5185358901764789 					 0.5185358901764789 
Iteration 18 	 0.5185358901764789 					 0.5185358901764789 
Iteration 19 	 0.5185358901764789 					 0.5185358901764789 
Iteration 20 	 0.5185358901764789 					 0.5185358901764789 
Iteration 21 	 0.5185358901764789 					 0.5185358901764789 
Iteration 22 	 0.5185358901764789 					 0.5185358901764789 
Iteration 23 	 0.5185358901764789 					 0.5185358901764789 
Iteration 24 	 0.5185358901764789 					 0.5185358901764789 
Iteration 25 	 0.5185358901764789 					 0.5185358901764789 
Iteration 26 	 0.5185358901764789 					 0.5185358901764789 
Iteration 27 	 0.5185358901764789 					 0.5185358901764789 
Iteration 28 	 0.5185358901764789 					 0.5185358901764789 
Iteration 29 	 0.5185358901764789 					 0.5185358901764789 
Iteration 30 	 0.5185358901764789 					 0.5185358901764789 
Iteration 31 	 0.5185358901764789 					 0.5185358901764789 
Iteration 32 	 0.5185358901764789 					 0.5185358901764789 
Iteration 33 	 0.5185358901764789 					 0.5185358901764789 
Iteration 34 	 0.5185358901764789 					 0.5185358901764789 
Iteration 35 	 0.5185358901764789 					 0.5185358901764789 
Iteration 36 	 0.5185358901764789 					 0.5185358901764789 
Iteration 37 	 0.5185358901764789 					 0.5185358901764789 
Iteration 38 	 0.5185358901764789 					 0.5185358901764789 
Iteration 39 	 0.5185358901764789 					 0.5185358901764789 
Iteration 40 	 0.5185358901764789 					 0.5185358901764789 
Iteration 41 	 0.5185358901764789 					 0.5185358901764789 
Iteration 42 	 0.5185358901764789 					 0.5185358901764789 
Iteration 43 	 0.5185358901764789 					 0.5185358901764789 
Iteration 44 	 0.5185358901764789 					 0.5185358901764789 
Iteration 45 	 0.5185358901764789 					 0.5185358901764789 
Iteration 46 	 0.5185358901764789 					 0.5185358901764789 
Iteration 47 	 0.5185358901764789 					 0.5185358901764789 
Iteration 48 	 0.5185358901764789 					 0.5185358901764789 
Iteration 49 	 0.5185358901764789 					 0.5185358901764789 


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Run Number - 18
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.533975069200054 					 0.533975069200054 
Iteration 1 	 0.5202950099720417 					 0.533975069200054 
Iteration 2 	 0.5191032807266841 					 0.533975069200054 
Iteration 3 	 0.5247977871629232 					 0.533975069200054 
Iteration 4 	 0.5208365750751347 					 0.533975069200054 
Iteration 5 	 0.525199057619982 					 0.533975069200054 
Iteration 6 	 0.5245813971746504 					 0.533975069200054 
Iteration 7 	 0.530818351035881 					 0.533975069200054 
Iteration 8 	 0.5360592391573052 					 0.5360592391573052 
Iteration 9 	 0.5357380913818593 					 0.5360592391573052 
Iteration 10 	 0.5431323376560482 					 0.5431323376560482 
Iteration 11 	 0.5476555127979508 					 0.5476555127979508 
Iteration 12 	 0.5497941708369958 					 0.5497941708369958 
Iteration 13 	 0.5507685985647843 					 0.5507685985647843 
Iteration 14 	 0.5514799113597134 					 0.5514799113597134 
Iteration 15 	 0.5515612145007672 					 0.5515612145007672 
Iteration 16 	 0.5515612145007672 					 0.5515612145007672 
Iteration 17 	 0.5515612145007672 					 0.5515612145007672 
Iteration 18 	 0.5524912084636163 					 0.5524912084636163 
Iteration 19 	 0.5524912084636163 					 0.5524912084636163 
Iteration 20 	 0.5524912084636163 					 0.5524912084636163 
Iteration 21 	 0.5524912084636163 					 0.5524912084636163 
Iteration 22 	 0.5524912084636163 					 0.5524912084636163 
Iteration 23 	 0.5524912084636163 					 0.5524912084636163 
Iteration 24 	 0.5524912084636163 					 0.5524912084636163 
Iteration 25 	 0.5524912084636163 					 0.5524912084636163 
Iteration 26 	 0.5524912084636163 					 0.5524912084636163 
Iteration 27 	 0.5524912084636163 					 0.5524912084636163 
Iteration 28 	 0.5524912084636163 					 0.5524912084636163 
Iteration 29 	 0.5524912084636163 					 0.5524912084636163 
Iteration 30 	 0.5524912084636163 					 0.5524912084636163 
Iteration 31 	 0.5524912084636163 					 0.5524912084636163 
Iteration 32 	 0.5524912084636163 					 0.5524912084636163 
Iteration 33 	 0.5524912084636163 					 0.5524912084636163 
Iteration 34 	 0.5524912084636163 					 0.5524912084636163 
Iteration 35 	 0.5524912084636163 					 0.5524912084636163 
Iteration 36 	 0.5524912084636163 					 0.5524912084636163 
Iteration 37 	 0.5524912084636163 					 0.5524912084636163 
Iteration 38 	 0.5524912084636163 					 0.5524912084636163 
Iteration 39 	 0.5524912084636163 					 0.5524912084636163 
Iteration 40 	 0.5524912084636163 					 0.5524912084636163 
Iteration 41 	 0.5524912084636163 					 0.5524912084636163 
Iteration 42 	 0.5524912084636163 					 0.5524912084636163 
Iteration 43 	 0.5524912084636163 					 0.5524912084636163 
Iteration 44 	 0.5524912084636163 					 0.5524912084636163 
Iteration 45 	 0.5524912084636163 					 0.5524912084636163 
Iteration 46 	 0.5524912084636163 					 0.5524912084636163 
Iteration 47 	 0.5524912084636163 					 0.5524912084636163 
Iteration 48 	 0.5524912084636163 					 0.5524912084636163 
Iteration 49 	 0.5524912084636163 					 0.5524912084636163 


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Run Number - 19
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5241874497524777 					 0.5241874497524777 
Iteration 1 	 0.5297760686092884 					 0.5297760686092884 
Iteration 2 	 0.5315034971770871 					 0.5315034971770871 
Iteration 3 	 0.5381057494199454 					 0.5381057494199454 
Iteration 4 	 0.5337822667288178 					 0.5381057494199454 
Iteration 5 	 0.5361912427536928 					 0.5381057494199454 
Iteration 6 	 0.538071742161095 					 0.5381057494199454 
Iteration 7 	 0.5371598139447186 					 0.5381057494199454 
Iteration 8 	 0.537300231200671 					 0.5381057494199454 
Iteration 9 	 0.5460431556184545 					 0.5460431556184545 
Iteration 10 	 0.5460431556184545 					 0.5460431556184545 
Iteration 11 	 0.5460431556184545 					 0.5460431556184545 
Iteration 12 	 0.5460009849720961 					 0.5460431556184545 
Iteration 13 	 0.5489245699660714 					 0.5489245699660714 
Iteration 14 	 0.5491240473309471 					 0.5491240473309471 
Iteration 15 	 0.5497175843519927 					 0.5497175843519927 
Iteration 16 	 0.5497175843519927 					 0.5497175843519927 
Iteration 17 	 0.5497175843519927 					 0.5497175843519927 
Iteration 18 	 0.5497175843519927 					 0.5497175843519927 
Iteration 19 	 0.5497175843519927 					 0.5497175843519927 
Iteration 20 	 0.5497175843519927 					 0.5497175843519927 
Iteration 21 	 0.5497175843519927 					 0.5497175843519927 
Iteration 22 	 0.5497175843519927 					 0.5497175843519927 
Iteration 23 	 0.5497175843519927 					 0.5497175843519927 
Iteration 24 	 0.5497175843519927 					 0.5497175843519927 
Iteration 25 	 0.5497175843519927 					 0.5497175843519927 
Iteration 26 	 0.5497175843519927 					 0.5497175843519927 
Iteration 27 	 0.5497175843519927 					 0.5497175843519927 
Iteration 28 	 0.5497175843519927 					 0.5497175843519927 
Iteration 29 	 0.5497175843519927 					 0.5497175843519927 
Iteration 30 	 0.5497175843519927 					 0.5497175843519927 
Iteration 31 	 0.5497175843519927 					 0.5497175843519927 
Iteration 32 	 0.5497175843519927 					 0.5497175843519927 
Iteration 33 	 0.5497175843519927 					 0.5497175843519927 
Iteration 34 	 0.5497175843519927 					 0.5497175843519927 
Iteration 35 	 0.5497175843519927 					 0.5497175843519927 
Iteration 36 	 0.5497175843519927 					 0.5497175843519927 
Iteration 37 	 0.5497175843519927 					 0.5497175843519927 
Iteration 38 	 0.5497175843519927 					 0.5497175843519927 
Iteration 39 	 0.5497175843519927 					 0.5497175843519927 
Iteration 40 	 0.5497175843519927 					 0.5497175843519927 
Iteration 41 	 0.5497175843519927 					 0.5497175843519927 
Iteration 42 	 0.5497175843519927 					 0.5497175843519927 
Iteration 43 	 0.5497175843519927 					 0.5497175843519927 
Iteration 44 	 0.5497175843519927 					 0.5497175843519927 
Iteration 45 	 0.5497175843519927 					 0.5497175843519927 
Iteration 46 	 0.5497175843519927 					 0.5497175843519927 
Iteration 47 	 0.5497175843519927 					 0.5497175843519927 
Iteration 48 	 0.5497175843519927 					 0.5497175843519927 
Iteration 49 	 0.5497175843519927 					 0.5497175843519927 


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Run Number - 20
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.5047227178767619 					 0.5047227178767619 
Iteration 1 	 0.4986901623602107 					 0.5047227178767619 
Iteration 2 	 0.5174592235568837 					 0.5174592235568837 
Iteration 3 	 0.509369802680852 					 0.5174592235568837 
Iteration 4 	 0.5049722603815399 					 0.5174592235568837 
Iteration 5 	 0.5082647047946017 					 0.5174592235568837 
Iteration 6 	 0.5116483776307524 					 0.5174592235568837 
Iteration 7 	 0.5143549175018683 					 0.5174592235568837 
Iteration 8 	 0.5143549175018683 					 0.5174592235568837 
Iteration 9 	 0.5180261083976752 					 0.5180261083976752 
Iteration 10 	 0.5180261083976752 					 0.5180261083976752 
Iteration 11 	 0.517452045835642 					 0.5180261083976752 
Iteration 12 	 0.5160033866230319 					 0.5180261083976752 
Iteration 13 	 0.5160033866230319 					 0.5180261083976752 
Iteration 14 	 0.5160033866230319 					 0.5180261083976752 
Iteration 15 	 0.5160033866230319 					 0.5180261083976752 
Iteration 16 	 0.5160033866230319 					 0.5180261083976752 
Iteration 17 	 0.5160033866230319 					 0.5180261083976752 
Iteration 18 	 0.5160033866230319 					 0.5180261083976752 
Iteration 19 	 0.5160033866230319 					 0.5180261083976752 
Iteration 20 	 0.5160033866230319 					 0.5180261083976752 
Iteration 21 	 0.5160033866230319 					 0.5180261083976752 
Iteration 22 	 0.5160033866230319 					 0.5180261083976752 
Iteration 23 	 0.5160033866230319 					 0.5180261083976752 
Iteration 24 	 0.5160033866230319 					 0.5180261083976752 
Iteration 25 	 0.5160033866230319 					 0.5180261083976752 
Iteration 26 	 0.5160033866230319 					 0.5180261083976752 
Iteration 27 	 0.5160033866230319 					 0.5180261083976752 
Iteration 28 	 0.5160033866230319 					 0.5180261083976752 
Iteration 29 	 0.5160033866230319 					 0.5180261083976752 
Iteration 30 	 0.5160033866230319 					 0.5180261083976752 
Iteration 31 	 0.5160033866230319 					 0.5180261083976752 
Iteration 32 	 0.5160033866230319 					 0.5180261083976752 
Iteration 33 	 0.5160033866230319 					 0.5180261083976752 
Iteration 34 	 0.5160033866230319 					 0.5180261083976752 
Iteration 35 	 0.5160033866230319 					 0.5180261083976752 
Iteration 36 	 0.5160033866230319 					 0.5180261083976752 
Iteration 37 	 0.5160033866230319 					 0.5180261083976752 
Iteration 38 	 0.5160033866230319 					 0.5180261083976752 
Iteration 39 	 0.5160033866230319 					 0.5180261083976752 
Iteration 40 	 0.5160033866230319 					 0.5180261083976752 
Iteration 41 	 0.5160033866230319 					 0.5180261083976752 
Iteration 42 	 0.5160033866230319 					 0.5180261083976752 
Iteration 43 	 0.5160033866230319 					 0.5180261083976752 
Iteration 44 	 0.5160033866230319 					 0.5180261083976752 
Iteration 45 	 0.5160033866230319 					 0.5180261083976752 
Iteration 46 	 0.5160033866230319 					 0.5180261083976752 
Iteration 47 	 0.5160033866230319 					 0.5180261083976752 
Iteration 48 	 0.5160033866230319 					 0.5180261083976752 
Iteration 49 	 0.5160033866230319 					 0.5180261083976752


solutions_poly['best_solution']

{'run_id': 18,
 'best_score': 0.5524912084636163,
 'num_features': 258,
 'selected_features': ['apol',
  'naAromAtom',
  'nAromBond',
  'nC',
  'ATS1m',
  'ATS4m',
  'ATS5m',
  'ATS0v',
  'ATS2v',
  'ATS5v',
  'ATS7v',
  'ATS8v',
  'ATS2e',
  'ATS3e',
  'ATS4e',
  'ATS0p',
  'ATS1p',
  'ATS7p',
  'ATS0i',
  'ATS1i',
  'ATS3i',
  'ATS4i',
  'ATS7i',
  'ATS1s',
  'ATS3s',
  'ATS4s',
  'ATS5s',
  'ATS6s',
  'ATS8s',
  'AATS0m',
  'AATS3m',
  'AATS4m',
  'AATS5m',
  'AATS0v',
  'AATS2v',
  'AATS5v',
  'AATS7v',
  'AATS8v',
  'AATS3i',
  'AATS5i',
  'AATS2s',
  'AATS4s',
  'AATS5s',
  'AATS7s',
  'ATSC0m',
  'ATSC1m',
  'ATSC4m',
  'ATSC6m',
  'ATSC0v',
  'ATSC4v',
  'ATSC5v',
  'ATSC7v',
  'ATSC2e',
  'ATSC3e',
  'ATSC4e',
  'ATSC5e',
  'ATSC6e',
  'ATSC7e',
  'ATSC0p',
  'ATSC6p',
  'ATSC7p',
  'ATSC8p',
  'ATSC4i',
  'ATSC5i',
  'ATSC7i',
  'ATSC8i',
  'ATSC1s',
  'ATSC2s',
  'ATSC3s',
  'ATSC6s',
  'ATSC7s',
  'ATSC8s',
  'AATSC2m',
  'AATSC5m',
  'AATSC0v',
  'AATSC2v',
  'AATSC8v',
  'SpAbs_DzZ',
  'EE_DzZ',
  'VE3_DzZ',
  'SpMAD_Dzm',
  'VR1_Dzm',
  'VR2_Dzm',
  'VR3_Dzm',
  'SpAbs_Dzv',
  'SpMax_Dzv',
  'SM1_Dzv',
  'VE3_Dzv',
  'VR1_Dzv',
  'VR2_Dzv',
  'VR3_Dzv',
  'SpAbs_Dze',
  'VE3_Dze',
  'VR1_Dze',
  'SpMax_Dzp',
  'SpDiam_Dzp',
  'SpAD_Dzp',
  'SpMAD_Dzp',
  'EE_Dzp',
  'SM1_Dzp',
  'VE3_Dzp',
  'SpMAD_Dzi',
  'VR3_Dzi',
  'SpAbs_Dzs',
  'SpMax_Dzs',
  'SpDiam_Dzs',
  'EE_Dzs',
  'VR3_Dzs',
  'BCUTp-1h',
  'nBonds',
  'nBonds2',
  'nBondsS2',
  'nBondsS3',
  'nBondsD',
  'nBondsD2',
  'C1SP2',
  'C2SP2',
  'C3SP2',
  'C2SP3',
  'C3SP3',
  'SPC-6',
  'VPC-4',
  'VPC-5',
  'SP-4',
  'SP-7',
  'VP-3',
  'VP-4',
  'Sse',
  'Si',
  'CrippenMR',
  'SpDiam_Dt',
  'EE_Dt',
  'VR1_Dt',
  'nHBa',
  'nHBint2',
  'nHBint3',
  'nHBint4',
  'nHBint7',
  'nHBint10',
  'nHssNH',
  'nHdsCH',
  'nHaaCH',
  'nHCsatu',
  'ndsCH',
  'naaCH',
  'ndssC',
  'naaaC',
  'nssNH',
  'naaN',
  'nsssN',
  'nssO',
  'SHBint2',
  'SHBint3',
  'SHBint5',
  'SHBint8',
  'SHBint9',
  'SHaaCH',
  'SHCsats',
  'SHCsatu',
  'SdsCH',
  'SaaCH',
  'SsssCH',
  'SaaaC',
  'SssssC',
  'SdNH',
  'SssNH',
  'SdsN',
  'SsssN',
  'SdO',
  'SaaO',
  'SsF',
  'SddssS',
  'minHBa',
  'minHBint3',
  'minHBint4',
  'minHBint5',
  'minHBint8',
  'minHBint9',
  'mindNH',
  'minssNH',
  'minaaN',
  'minssO',
  'minddssS',
  'maxHBint3',
  'maxHBint4',
  'maxHBint8',
  'maxsCH3',
  'maxdsCH',
  'maxssNH',
  'maxdsN',
  'maxaaN',
  'maxsssN',
  'maxaaO',
  'maxsF',
  'gmin',
  'MAXDN',
  'MAXDN2',
  'MAXDP2',
  'DELS2',
  'ETA_Beta',
  'ETA_Beta_s',
  'ETA_Beta_ns_d',
  'ETA_Eta_F',
  'ETA_Eta_R_L',
  'fragC',
  'nHBAcc3',
  'nHBAcc_Lipinski',
  'nHBDon_Lipinski',
  'TIC0',
  'TIC1',
  'TIC3',
  'TIC4',
  'MIC0',
  'MIC1',
  'MIC2',
  'ZMIC0',
  'ZMIC1',
  'ZMIC5',
  'Kier2',
  'nAtomP',
  'MDEC-11',
  'MDEC-12',
  'MDEC-13',
  'MDEC-22',
  'MDEC-34',
  'MDEN-22',
  'MLFER_BH',
  'MLFER_L',
  'MPC3',
  'MPC4',
  'MPC6',
  'MPC7',
  'TPC',
  'piPC9',
  'piPC10',
  'R_TpiPCTPC',
  'nRing',
  'n6Ring',
  'nTRing',
  'n6HeteroRing',
  'nRotBt',
  'LipinskiFailures',
  'GGI1',
  'GGI3',
  'SpAD_D',
  'SpMAD_D',
  'VE3_D',
  'VR2_D',
  'VR3_D',
  'TopoPSA',
  'VABC',
  'SRW7',
  'MW',
  'AMW',
  'WTPT-4',
  'WPATH',
  'WPOL',
  'Zagreb'],
 'plot': Figure({
     'data': [{'mode': 'markers',
               'name': 'objective_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.533975069200054, 0.5202950099720417, 0.5191032807266841,
                           0.5247977871629232, 0.5208365750751347, 0.525199057619982,
                           0.5245813971746504, 0.530818351035881, 0.5360592391573052,
                           0.5357380913818593, 0.5431323376560482, 0.5476555127979508,
                           0.5497941708369958, 0.5507685985647843, 0.5514799113597134,
                           0.5515612145007672, 0.5515612145007672, 0.5515612145007672,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163], dtype=object)},
              {'mode': 'lines+markers',
               'name': 'best_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.533975069200054, 0.533975069200054, 0.533975069200054,
                           0.533975069200054, 0.533975069200054, 0.533975069200054,
                           0.533975069200054, 0.533975069200054, 0.5360592391573052,
                           0.5360592391573052, 0.5431323376560482, 0.5476555127979508,
                           0.5497941708369958, 0.5507685985647843, 0.5514799113597134,
                           0.5515612145007672, 0.5515612145007672, 0.5515612145007672,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163, 0.5524912084636163,
                           0.5524912084636163, 0.5524912084636163], dtype=object)}],
     'layout': {'template': '...',
                'title': {'text': 'Optimization History Plot'},
                'xaxis': {'title': {'text': 'Iteration'}},
                'yaxis': {'title': {'text': 'objective_score'}}}
 })}


solutions_poly['best_solution']['plot']


# Define machine learning model
svr_sigmoid_model = SVR(kernel='sigmoid')
# Multiple run GA with those machine learning model
solutions_sigmoid = multiple_run_fs(20, svr_sigmoid_model, X_train, y_train, X_valid, y_valid)


 ----------------------------------------------------------------------------------------
Run Number - 1
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.35292058051261554 					 0.35292058051261554 
Iteration 1 	 0.4241619077387876 					 0.4241619077387876 
Iteration 2 	 0.39865581862358324 					 0.4241619077387876 
Iteration 3 	 0.42954734479534007 					 0.42954734479534007 
Iteration 4 	 0.4009524142712858 					 0.42954734479534007 
Iteration 5 	 0.39865581862358324 					 0.42954734479534007 
Iteration 6 	 0.40457424183358626 					 0.42954734479534007 
Iteration 7 	 0.41767608461972905 					 0.42954734479534007 
Iteration 8 	 0.41767608461972905 					 0.42954734479534007 
Iteration 9 	 0.41767608461972905 					 0.42954734479534007 
Iteration 10 	 0.41767608461972905 					 0.42954734479534007 
Iteration 11 	 0.41767608461972905 					 0.42954734479534007 
Iteration 12 	 0.41767608461972905 					 0.42954734479534007 
Iteration 13 	 0.41767608461972905 					 0.42954734479534007 
Iteration 14 	 0.41767608461972905 					 0.42954734479534007 
Iteration 15 	 0.41767608461972905 					 0.42954734479534007 
Iteration 16 	 0.41767608461972905 					 0.42954734479534007 
Iteration 17 	 0.41767608461972905 					 0.42954734479534007 
Iteration 18 	 0.41767608461972905 					 0.42954734479534007 
Iteration 19 	 0.41767608461972905 					 0.42954734479534007 
Iteration 20 	 0.41767608461972905 					 0.42954734479534007 
Iteration 21 	 0.41767608461972905 					 0.42954734479534007 
Iteration 22 	 0.41767608461972905 					 0.42954734479534007 
Iteration 23 	 0.41767608461972905 					 0.42954734479534007 
Iteration 24 	 0.41767608461972905 					 0.42954734479534007 
Iteration 25 	 0.41767608461972905 					 0.42954734479534007 
Iteration 26 	 0.41767608461972905 					 0.42954734479534007 
Iteration 27 	 0.41767608461972905 					 0.42954734479534007 
Iteration 28 	 0.41767608461972905 					 0.42954734479534007 
Iteration 29 	 0.41767608461972905 					 0.42954734479534007 
Iteration 30 	 0.41767608461972905 					 0.42954734479534007 
Iteration 31 	 0.41767608461972905 					 0.42954734479534007 
Iteration 32 	 0.41767608461972905 					 0.42954734479534007 
Iteration 33 	 0.41767608461972905 					 0.42954734479534007 
Iteration 34 	 0.41767608461972905 					 0.42954734479534007 
Iteration 35 	 0.41767608461972905 					 0.42954734479534007 
Iteration 36 	 0.41767608461972905 					 0.42954734479534007 
Iteration 37 	 0.41767608461972905 					 0.42954734479534007 
Iteration 38 	 0.41767608461972905 					 0.42954734479534007 
Iteration 39 	 0.41767608461972905 					 0.42954734479534007 
Iteration 40 	 0.41767608461972905 					 0.42954734479534007 
Iteration 41 	 0.41767608461972905 					 0.42954734479534007 
Iteration 42 	 0.41767608461972905 					 0.42954734479534007 
Iteration 43 	 0.41767608461972905 					 0.42954734479534007 
Iteration 44 	 0.41767608461972905 					 0.42954734479534007 
Iteration 45 	 0.41767608461972905 					 0.42954734479534007 
Iteration 46 	 0.41767608461972905 					 0.42954734479534007 
Iteration 47 	 0.41767608461972905 					 0.42954734479534007 
Iteration 48 	 0.41767608461972905 					 0.42954734479534007 
Iteration 49 	 0.41767608461972905 					 0.42954734479534007 


 ----------------------------------------------------------------------------------------
Run Number - 2
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.3610078158831266 					 0.3610078158831266 
Iteration 1 	 0.45338204506678526 					 0.45338204506678526 
Iteration 2 	 0.3940960744866534 					 0.45338204506678526 
Iteration 3 	 0.3940960744866534 					 0.45338204506678526 
Iteration 4 	 0.43721865615421207 					 0.45338204506678526 
Iteration 5 	 0.43721865615421207 					 0.45338204506678526 
Iteration 6 	 0.43721865615421207 					 0.45338204506678526 
Iteration 7 	 0.43721865615421207 					 0.45338204506678526 
Iteration 8 	 0.43720894416637646 					 0.45338204506678526 
Iteration 9 	 0.43720894416637646 					 0.45338204506678526 
Iteration 10 	 0.43720894416637646 					 0.45338204506678526 
Iteration 11 	 0.43720894416637646 					 0.45338204506678526 
Iteration 12 	 0.43720894416637646 					 0.45338204506678526 
Iteration 13 	 0.43720894416637646 					 0.45338204506678526 
Iteration 14 	 0.43720894416637646 					 0.45338204506678526 
Iteration 15 	 0.43720894416637646 					 0.45338204506678526 
Iteration 16 	 0.43720894416637646 					 0.45338204506678526 
Iteration 17 	 0.43720894416637646 					 0.45338204506678526 
Iteration 18 	 0.43720894416637646 					 0.45338204506678526 
Iteration 19 	 0.43720894416637646 					 0.45338204506678526 
Iteration 20 	 0.43720894416637646 					 0.45338204506678526 
Iteration 21 	 0.43720894416637646 					 0.45338204506678526 
Iteration 22 	 0.43720894416637646 					 0.45338204506678526 
Iteration 23 	 0.43720894416637646 					 0.45338204506678526 
Iteration 24 	 0.43720894416637646 					 0.45338204506678526 
Iteration 25 	 0.43720894416637646 					 0.45338204506678526 
Iteration 26 	 0.43720894416637646 					 0.45338204506678526 
Iteration 27 	 0.43720894416637646 					 0.45338204506678526 
Iteration 28 	 0.43720894416637646 					 0.45338204506678526 
Iteration 29 	 0.43720894416637646 					 0.45338204506678526 
Iteration 30 	 0.43720894416637646 					 0.45338204506678526 
Iteration 31 	 0.43720894416637646 					 0.45338204506678526 
Iteration 32 	 0.43720894416637646 					 0.45338204506678526 
Iteration 33 	 0.43720894416637646 					 0.45338204506678526 
Iteration 34 	 0.43720894416637646 					 0.45338204506678526 
Iteration 35 	 0.43720894416637646 					 0.45338204506678526 
Iteration 36 	 0.43720894416637646 					 0.45338204506678526 
Iteration 37 	 0.43720894416637646 					 0.45338204506678526 
Iteration 38 	 0.43720894416637646 					 0.45338204506678526 
Iteration 39 	 0.43720894416637646 					 0.45338204506678526 
Iteration 40 	 0.43720894416637646 					 0.45338204506678526 
Iteration 41 	 0.43720894416637646 					 0.45338204506678526 
Iteration 42 	 0.43720894416637646 					 0.45338204506678526 
Iteration 43 	 0.43720894416637646 					 0.45338204506678526 
Iteration 44 	 0.43720894416637646 					 0.45338204506678526 
Iteration 45 	 0.43720894416637646 					 0.45338204506678526 
Iteration 46 	 0.43720894416637646 					 0.45338204506678526 
Iteration 47 	 0.43720894416637646 					 0.45338204506678526 
Iteration 48 	 0.43720894416637646 					 0.45338204506678526 
Iteration 49 	 0.43720894416637646 					 0.45338204506678526 


 ----------------------------------------------------------------------------------------
Run Number - 3
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.36955577186236105 					 0.36955577186236105 
Iteration 1 	 0.3800828275628093 					 0.3800828275628093 
Iteration 2 	 0.3807618344262117 					 0.3807618344262117 
Iteration 3 	 0.40940226709420446 					 0.40940226709420446 
Iteration 4 	 0.4023019161583719 					 0.40940226709420446 
Iteration 5 	 0.4023019161583719 					 0.40940226709420446 
Iteration 6 	 0.4428600634933584 					 0.4428600634933584 
Iteration 7 	 0.4420153148723352 					 0.4428600634933584 
Iteration 8 	 0.44460117190310056 					 0.44460117190310056 
Iteration 9 	 0.478837200382175 					 0.478837200382175 
Iteration 10 	 0.47281759558847014 					 0.478837200382175 
Iteration 11 	 0.47281759558847014 					 0.478837200382175 
Iteration 12 	 0.47281759558847014 					 0.478837200382175 
Iteration 13 	 0.47281759558847014 					 0.478837200382175 
Iteration 14 	 0.4867647023511467 					 0.4867647023511467 
Iteration 15 	 0.4867647023511467 					 0.4867647023511467 
Iteration 16 	 0.4867647023511467 					 0.4867647023511467 
Iteration 17 	 0.4867647023511467 					 0.4867647023511467 
Iteration 18 	 0.4867647023511467 					 0.4867647023511467 
Iteration 19 	 0.4867647023511467 					 0.4867647023511467 
Iteration 20 	 0.4867647023511467 					 0.4867647023511467 
Iteration 21 	 0.4867647023511467 					 0.4867647023511467 
Iteration 22 	 0.4867647023511467 					 0.4867647023511467 
Iteration 23 	 0.4867647023511467 					 0.4867647023511467 
Iteration 24 	 0.4867647023511467 					 0.4867647023511467 
Iteration 25 	 0.4867647023511467 					 0.4867647023511467 
Iteration 26 	 0.4867647023511467 					 0.4867647023511467 
Iteration 27 	 0.4867647023511467 					 0.4867647023511467 
Iteration 28 	 0.4867647023511467 					 0.4867647023511467 
Iteration 29 	 0.4867647023511467 					 0.4867647023511467 
Iteration 30 	 0.4867647023511467 					 0.4867647023511467 
Iteration 31 	 0.4867647023511467 					 0.4867647023511467 
Iteration 32 	 0.4867647023511467 					 0.4867647023511467 
Iteration 33 	 0.4867647023511467 					 0.4867647023511467 
Iteration 34 	 0.4867647023511467 					 0.4867647023511467 
Iteration 35 	 0.4867647023511467 					 0.4867647023511467 
Iteration 36 	 0.4867647023511467 					 0.4867647023511467 
Iteration 37 	 0.4867647023511467 					 0.4867647023511467 
Iteration 38 	 0.4867647023511467 					 0.4867647023511467 
Iteration 39 	 0.4867647023511467 					 0.4867647023511467 
Iteration 40 	 0.4867647023511467 					 0.4867647023511467 
Iteration 41 	 0.4867647023511467 					 0.4867647023511467 
Iteration 42 	 0.4867647023511467 					 0.4867647023511467 
Iteration 43 	 0.4867647023511467 					 0.4867647023511467 
Iteration 44 	 0.4867647023511467 					 0.4867647023511467 
Iteration 45 	 0.4867647023511467 					 0.4867647023511467 
Iteration 46 	 0.4867647023511467 					 0.4867647023511467 
Iteration 47 	 0.4867647023511467 					 0.4867647023511467 
Iteration 48 	 0.4867647023511467 					 0.4867647023511467 
Iteration 49 	 0.4867647023511467 					 0.4867647023511467 


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Run Number - 4
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.3625025858531068 					 0.3625025858531068 
Iteration 1 	 0.38463555675594585 					 0.38463555675594585 
Iteration 2 	 0.36986242748392173 					 0.38463555675594585 
Iteration 3 	 0.410559924449819 					 0.410559924449819 
Iteration 4 	 0.410559924449819 					 0.410559924449819 
Iteration 5 	 0.4428949323592868 					 0.4428949323592868 
Iteration 6 	 0.4406893981903693 					 0.4428949323592868 
Iteration 7 	 0.4406893981903693 					 0.4428949323592868 
Iteration 8 	 0.45520264025292295 					 0.45520264025292295 
Iteration 9 	 0.46175940959516565 					 0.46175940959516565 
Iteration 10 	 0.45520264025292295 					 0.46175940959516565 
Iteration 11 	 0.4708285380929559 					 0.4708285380929559 
Iteration 12 	 0.4708285380929559 					 0.4708285380929559 
Iteration 13 	 0.4708285380929559 					 0.4708285380929559 
Iteration 14 	 0.4739165646617304 					 0.4739165646617304 
Iteration 15 	 0.4739165646617304 					 0.4739165646617304 
Iteration 16 	 0.4739165646617304 					 0.4739165646617304 
Iteration 17 	 0.4739165646617304 					 0.4739165646617304 
Iteration 18 	 0.4739165646617304 					 0.4739165646617304 
Iteration 19 	 0.4739165646617304 					 0.4739165646617304 
Iteration 20 	 0.4739165646617304 					 0.4739165646617304 
Iteration 21 	 0.4739165646617304 					 0.4739165646617304 
Iteration 22 	 0.4739165646617304 					 0.4739165646617304 
Iteration 23 	 0.4739165646617304 					 0.4739165646617304 
Iteration 24 	 0.4739165646617304 					 0.4739165646617304 
Iteration 25 	 0.4739165646617304 					 0.4739165646617304 
Iteration 26 	 0.4739165646617304 					 0.4739165646617304 
Iteration 27 	 0.4739165646617304 					 0.4739165646617304 
Iteration 28 	 0.4739165646617304 					 0.4739165646617304 
Iteration 29 	 0.4739165646617304 					 0.4739165646617304 
Iteration 30 	 0.4739165646617304 					 0.4739165646617304 
Iteration 31 	 0.4739165646617304 					 0.4739165646617304 
Iteration 32 	 0.4739165646617304 					 0.4739165646617304 
Iteration 33 	 0.4739165646617304 					 0.4739165646617304 
Iteration 34 	 0.4739165646617304 					 0.4739165646617304 
Iteration 35 	 0.4739165646617304 					 0.4739165646617304 
Iteration 36 	 0.4739165646617304 					 0.4739165646617304 
Iteration 37 	 0.4739165646617304 					 0.4739165646617304 
Iteration 38 	 0.4739165646617304 					 0.4739165646617304 
Iteration 39 	 0.4739165646617304 					 0.4739165646617304 
Iteration 40 	 0.4739165646617304 					 0.4739165646617304 
Iteration 41 	 0.4739165646617304 					 0.4739165646617304 
Iteration 42 	 0.4739165646617304 					 0.4739165646617304 
Iteration 43 	 0.4739165646617304 					 0.4739165646617304 
Iteration 44 	 0.4739165646617304 					 0.4739165646617304 
Iteration 45 	 0.4739165646617304 					 0.4739165646617304 
Iteration 46 	 0.4739165646617304 					 0.4739165646617304 
Iteration 47 	 0.4739165646617304 					 0.4739165646617304 
Iteration 48 	 0.4739165646617304 					 0.4739165646617304 
Iteration 49 	 0.4739165646617304 					 0.4739165646617304 


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Run Number - 5
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.3555873826208331 					 0.3555873826208331 
Iteration 1 	 0.3550981109381085 					 0.3555873826208331 
Iteration 2 	 0.36263359727545813 					 0.36263359727545813 
Iteration 3 	 0.3580778232132933 					 0.36263359727545813 
Iteration 4 	 0.3623812672222789 					 0.36263359727545813 
Iteration 5 	 0.3623812672222789 					 0.36263359727545813 
Iteration 6 	 0.3623812672222789 					 0.36263359727545813 
Iteration 7 	 0.35628627865950024 					 0.36263359727545813 
Iteration 8 	 0.35552127599165845 					 0.36263359727545813 
Iteration 9 	 0.35552127599165845 					 0.36263359727545813 
Iteration 10 	 0.35592869247087455 					 0.36263359727545813 
Iteration 11 	 0.35592869247087455 					 0.36263359727545813 
Iteration 12 	 0.35592869247087455 					 0.36263359727545813 
Iteration 13 	 0.3581967462211152 					 0.36263359727545813 
Iteration 14 	 0.3581967462211152 					 0.36263359727545813 
Iteration 15 	 0.3581967462211152 					 0.36263359727545813 
Iteration 16 	 0.3581967462211152 					 0.36263359727545813 
Iteration 17 	 0.3581967462211152 					 0.36263359727545813 
Iteration 18 	 0.3581967462211152 					 0.36263359727545813 
Iteration 19 	 0.3581967462211152 					 0.36263359727545813 
Iteration 20 	 0.3581967462211152 					 0.36263359727545813 
Iteration 21 	 0.3581967462211152 					 0.36263359727545813 
Iteration 22 	 0.3581967462211152 					 0.36263359727545813 
Iteration 23 	 0.3581967462211152 					 0.36263359727545813 
Iteration 24 	 0.3581967462211152 					 0.36263359727545813 
Iteration 25 	 0.3581967462211152 					 0.36263359727545813 
Iteration 26 	 0.3581967462211152 					 0.36263359727545813 
Iteration 27 	 0.3581967462211152 					 0.36263359727545813 
Iteration 28 	 0.3581967462211152 					 0.36263359727545813 
Iteration 29 	 0.3581967462211152 					 0.36263359727545813 
Iteration 30 	 0.3581967462211152 					 0.36263359727545813 
Iteration 31 	 0.3581967462211152 					 0.36263359727545813 
Iteration 32 	 0.3581967462211152 					 0.36263359727545813 
Iteration 33 	 0.3581967462211152 					 0.36263359727545813 
Iteration 34 	 0.3581967462211152 					 0.36263359727545813 
Iteration 35 	 0.3581967462211152 					 0.36263359727545813 
Iteration 36 	 0.3581967462211152 					 0.36263359727545813 
Iteration 37 	 0.3581967462211152 					 0.36263359727545813 
Iteration 38 	 0.3581967462211152 					 0.36263359727545813 
Iteration 39 	 0.3581967462211152 					 0.36263359727545813 
Iteration 40 	 0.3581967462211152 					 0.36263359727545813 
Iteration 41 	 0.3581967462211152 					 0.36263359727545813 
Iteration 42 	 0.3581967462211152 					 0.36263359727545813 
Iteration 43 	 0.3581967462211152 					 0.36263359727545813 
Iteration 44 	 0.3581967462211152 					 0.36263359727545813 
Iteration 45 	 0.3581967462211152 					 0.36263359727545813 
Iteration 46 	 0.3581967462211152 					 0.36263359727545813 
Iteration 47 	 0.3581967462211152 					 0.36263359727545813 
Iteration 48 	 0.3581967462211152 					 0.36263359727545813 
Iteration 49 	 0.3581967462211152 					 0.36263359727545813 


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Run Number - 6
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.37956480042228025 					 0.37956480042228025 
Iteration 1 	 0.3683829064103701 					 0.37956480042228025 
Iteration 2 	 0.379694035729147 					 0.379694035729147 
Iteration 3 	 0.42793719628028104 					 0.42793719628028104 
Iteration 4 	 0.3866526157061767 					 0.42793719628028104 
Iteration 5 	 0.3852349708769866 					 0.42793719628028104 
Iteration 6 	 0.3702432207227931 					 0.42793719628028104 
Iteration 7 	 0.36862013619876893 					 0.42793719628028104 
Iteration 8 	 0.3936144585845518 					 0.42793719628028104 
Iteration 9 	 0.39559868009977106 					 0.42793719628028104 
Iteration 10 	 0.3936144585845518 					 0.42793719628028104 
Iteration 11 	 0.4029613256174193 					 0.42793719628028104 
Iteration 12 	 0.395320251347689 					 0.42793719628028104 
Iteration 13 	 0.4029613256174193 					 0.42793719628028104 
Iteration 14 	 0.4029613256174193 					 0.42793719628028104 
Iteration 15 	 0.4029613256174193 					 0.42793719628028104 
Iteration 16 	 0.4029613256174193 					 0.42793719628028104 
Iteration 17 	 0.4029613256174193 					 0.42793719628028104 
Iteration 18 	 0.3989584423619321 					 0.42793719628028104 
Iteration 19 	 0.3989584423619321 					 0.42793719628028104 
Iteration 20 	 0.4029613256174193 					 0.42793719628028104 
Iteration 21 	 0.4029613256174193 					 0.42793719628028104 
Iteration 22 	 0.4029613256174193 					 0.42793719628028104 
Iteration 23 	 0.4029613256174193 					 0.42793719628028104 
Iteration 24 	 0.4029613256174193 					 0.42793719628028104 
Iteration 25 	 0.4029613256174193 					 0.42793719628028104 
Iteration 26 	 0.4029613256174193 					 0.42793719628028104 
Iteration 27 	 0.4029613256174193 					 0.42793719628028104 
Iteration 28 	 0.4029613256174193 					 0.42793719628028104 
Iteration 29 	 0.4029613256174193 					 0.42793719628028104 
Iteration 30 	 0.4029613256174193 					 0.42793719628028104 
Iteration 31 	 0.4029613256174193 					 0.42793719628028104 
Iteration 32 	 0.4029613256174193 					 0.42793719628028104 
Iteration 33 	 0.4029613256174193 					 0.42793719628028104 
Iteration 34 	 0.4029613256174193 					 0.42793719628028104 
Iteration 35 	 0.4029613256174193 					 0.42793719628028104 
Iteration 36 	 0.4029613256174193 					 0.42793719628028104 
Iteration 37 	 0.4029613256174193 					 0.42793719628028104 
Iteration 38 	 0.4029613256174193 					 0.42793719628028104 
Iteration 39 	 0.4029613256174193 					 0.42793719628028104 
Iteration 40 	 0.4029613256174193 					 0.42793719628028104 
Iteration 41 	 0.4029613256174193 					 0.42793719628028104 
Iteration 42 	 0.4029613256174193 					 0.42793719628028104 
Iteration 43 	 0.4029613256174193 					 0.42793719628028104 
Iteration 44 	 0.4029613256174193 					 0.42793719628028104 
Iteration 45 	 0.4029613256174193 					 0.42793719628028104 
Iteration 46 	 0.4029613256174193 					 0.42793719628028104 
Iteration 47 	 0.4029613256174193 					 0.42793719628028104 
Iteration 48 	 0.4029613256174193 					 0.42793719628028104 
Iteration 49 	 0.4029613256174193 					 0.42793719628028104 


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Run Number - 7
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.3613950728626243 					 0.3613950728626243 
Iteration 1 	 0.3906476638214841 					 0.3906476638214841 
Iteration 2 	 0.36944066437098544 					 0.3906476638214841 
Iteration 3 	 0.4252338540261316 					 0.4252338540261316 
Iteration 4 	 0.42349020272031923 					 0.4252338540261316 
Iteration 5 	 0.42069535814048425 					 0.4252338540261316 
Iteration 6 	 0.4232547180335015 					 0.4252338540261316 
Iteration 7 	 0.4394941811216826 					 0.4394941811216826 
Iteration 8 	 0.435023349872042 					 0.4394941811216826 
Iteration 9 	 0.45370907192292065 					 0.45370907192292065 
Iteration 10 	 0.45370907192292065 					 0.45370907192292065 
Iteration 11 	 0.46524215719368833 					 0.46524215719368833 
Iteration 12 	 0.46524215719368833 					 0.46524215719368833 
Iteration 13 	 0.45831828020482973 					 0.46524215719368833 
Iteration 14 	 0.45644708279595947 					 0.46524215719368833 
Iteration 15 	 0.45644708279595947 					 0.46524215719368833 
Iteration 16 	 0.45644708279595947 					 0.46524215719368833 
Iteration 17 	 0.45644708279595947 					 0.46524215719368833 
Iteration 18 	 0.45644708279595947 					 0.46524215719368833 
Iteration 19 	 0.45644708279595947 					 0.46524215719368833 
Iteration 20 	 0.45644708279595947 					 0.46524215719368833 
Iteration 21 	 0.45644708279595947 					 0.46524215719368833 
Iteration 22 	 0.45644708279595947 					 0.46524215719368833 
Iteration 23 	 0.45644708279595947 					 0.46524215719368833 
Iteration 24 	 0.45644708279595947 					 0.46524215719368833 
Iteration 25 	 0.45644708279595947 					 0.46524215719368833 
Iteration 26 	 0.45644708279595947 					 0.46524215719368833 
Iteration 27 	 0.45644708279595947 					 0.46524215719368833 
Iteration 28 	 0.45644708279595947 					 0.46524215719368833 
Iteration 29 	 0.45644708279595947 					 0.46524215719368833 
Iteration 30 	 0.45644708279595947 					 0.46524215719368833 
Iteration 31 	 0.45644708279595947 					 0.46524215719368833 
Iteration 32 	 0.45644708279595947 					 0.46524215719368833 
Iteration 33 	 0.45644708279595947 					 0.46524215719368833 
Iteration 34 	 0.45644708279595947 					 0.46524215719368833 
Iteration 35 	 0.45644708279595947 					 0.46524215719368833 
Iteration 36 	 0.45644708279595947 					 0.46524215719368833 
Iteration 37 	 0.45644708279595947 					 0.46524215719368833 
Iteration 38 	 0.45644708279595947 					 0.46524215719368833 
Iteration 39 	 0.45644708279595947 					 0.46524215719368833 
Iteration 40 	 0.45644708279595947 					 0.46524215719368833 
Iteration 41 	 0.45644708279595947 					 0.46524215719368833 
Iteration 42 	 0.45644708279595947 					 0.46524215719368833 
Iteration 43 	 0.45644708279595947 					 0.46524215719368833 
Iteration 44 	 0.45644708279595947 					 0.46524215719368833 
Iteration 45 	 0.45644708279595947 					 0.46524215719368833 
Iteration 46 	 0.45644708279595947 					 0.46524215719368833 
Iteration 47 	 0.45644708279595947 					 0.46524215719368833 
Iteration 48 	 0.45644708279595947 					 0.46524215719368833 
Iteration 49 	 0.45644708279595947 					 0.46524215719368833 


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Run Number - 8
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.38032678228466943 					 0.38032678228466943 
Iteration 1 	 0.3592184909337865 					 0.38032678228466943 
Iteration 2 	 0.3592184909337865 					 0.38032678228466943 
Iteration 3 	 0.3908502399977187 					 0.3908502399977187 
Iteration 4 	 0.40183400114652357 					 0.40183400114652357 
Iteration 5 	 0.4128691454373651 					 0.4128691454373651 
Iteration 6 	 0.42741707009644436 					 0.42741707009644436 
Iteration 7 	 0.42741707009644436 					 0.42741707009644436 
Iteration 8 	 0.42741707009644436 					 0.42741707009644436 
Iteration 9 	 0.42741707009644436 					 0.42741707009644436 
Iteration 10 	 0.4376834560459594 					 0.4376834560459594 
Iteration 11 	 0.4376834560459594 					 0.4376834560459594 
Iteration 12 	 0.43119191488751674 					 0.4376834560459594 
Iteration 13 	 0.4376834560459594 					 0.4376834560459594 
Iteration 14 	 0.4376834560459594 					 0.4376834560459594 
Iteration 15 	 0.4376834560459594 					 0.4376834560459594 
Iteration 16 	 0.4365001178636339 					 0.4376834560459594 
Iteration 17 	 0.4365001178636339 					 0.4376834560459594 
Iteration 18 	 0.4365001178636339 					 0.4376834560459594 
Iteration 19 	 0.4365001178636339 					 0.4376834560459594 
Iteration 20 	 0.4365001178636339 					 0.4376834560459594 
Iteration 21 	 0.4365001178636339 					 0.4376834560459594 
Iteration 22 	 0.4365001178636339 					 0.4376834560459594 
Iteration 23 	 0.4365001178636339 					 0.4376834560459594 
Iteration 24 	 0.4365001178636339 					 0.4376834560459594 
Iteration 25 	 0.4365001178636339 					 0.4376834560459594 
Iteration 26 	 0.4365001178636339 					 0.4376834560459594 
Iteration 27 	 0.4365001178636339 					 0.4376834560459594 
Iteration 28 	 0.4365001178636339 					 0.4376834560459594 
Iteration 29 	 0.4365001178636339 					 0.4376834560459594 
Iteration 30 	 0.4365001178636339 					 0.4376834560459594 
Iteration 31 	 0.4365001178636339 					 0.4376834560459594 
Iteration 32 	 0.4365001178636339 					 0.4376834560459594 
Iteration 33 	 0.4365001178636339 					 0.4376834560459594 
Iteration 34 	 0.4365001178636339 					 0.4376834560459594 
Iteration 35 	 0.4365001178636339 					 0.4376834560459594 
Iteration 36 	 0.4365001178636339 					 0.4376834560459594 
Iteration 37 	 0.4365001178636339 					 0.4376834560459594 
Iteration 38 	 0.4365001178636339 					 0.4376834560459594 
Iteration 39 	 0.4365001178636339 					 0.4376834560459594 
Iteration 40 	 0.4365001178636339 					 0.4376834560459594 
Iteration 41 	 0.4365001178636339 					 0.4376834560459594 
Iteration 42 	 0.4365001178636339 					 0.4376834560459594 
Iteration 43 	 0.4365001178636339 					 0.4376834560459594 
Iteration 44 	 0.4365001178636339 					 0.4376834560459594 
Iteration 45 	 0.4365001178636339 					 0.4376834560459594 
Iteration 46 	 0.4365001178636339 					 0.4376834560459594 
Iteration 47 	 0.4365001178636339 					 0.4376834560459594 
Iteration 48 	 0.4365001178636339 					 0.4376834560459594 
Iteration 49 	 0.4365001178636339 					 0.4376834560459594 


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Run Number - 9
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.3482157515934455 					 0.3482157515934455 
Iteration 1 	 0.37161364818737386 					 0.37161364818737386 
Iteration 2 	 0.36205418514028054 					 0.37161364818737386 
Iteration 3 	 0.36205418514028054 					 0.37161364818737386 
Iteration 4 	 0.36289506678264893 					 0.37161364818737386 
Iteration 5 	 0.3488903966077621 					 0.37161364818737386 
Iteration 6 	 0.3553080447217999 					 0.37161364818737386 
Iteration 7 	 0.3581382666786815 					 0.37161364818737386 
Iteration 8 	 0.3966400833756608 					 0.3966400833756608 
Iteration 9 	 0.3672745015983703 					 0.3966400833756608 
Iteration 10 	 0.3740223316369721 					 0.3966400833756608 
Iteration 11 	 0.37996231863331464 					 0.3966400833756608 
Iteration 12 	 0.37996231863331464 					 0.3966400833756608 
Iteration 13 	 0.36894243207473254 					 0.3966400833756608 
Iteration 14 	 0.3755163021261003 					 0.3966400833756608 
Iteration 15 	 0.36894243207473254 					 0.3966400833756608 
Iteration 16 	 0.3811956363971122 					 0.3966400833756608 
Iteration 17 	 0.3811956363971122 					 0.3966400833756608 
Iteration 18 	 0.3811956363971122 					 0.3966400833756608 
Iteration 19 	 0.3811956363971122 					 0.3966400833756608 
Iteration 20 	 0.3811956363971122 					 0.3966400833756608 
Iteration 21 	 0.3811956363971122 					 0.3966400833756608 
Iteration 22 	 0.3811956363971122 					 0.3966400833756608 
Iteration 23 	 0.3811956363971122 					 0.3966400833756608 
Iteration 24 	 0.3811956363971122 					 0.3966400833756608 
Iteration 25 	 0.3811956363971122 					 0.3966400833756608 
Iteration 26 	 0.3811956363971122 					 0.3966400833756608 
Iteration 27 	 0.3811956363971122 					 0.3966400833756608 
Iteration 28 	 0.3811956363971122 					 0.3966400833756608 
Iteration 29 	 0.3811956363971122 					 0.3966400833756608 
Iteration 30 	 0.3811956363971122 					 0.3966400833756608 
Iteration 31 	 0.3811956363971122 					 0.3966400833756608 
Iteration 32 	 0.3811956363971122 					 0.3966400833756608 
Iteration 33 	 0.3811956363971122 					 0.3966400833756608 
Iteration 34 	 0.3811956363971122 					 0.3966400833756608 
Iteration 35 	 0.3811956363971122 					 0.3966400833756608 
Iteration 36 	 0.3811956363971122 					 0.3966400833756608 
Iteration 37 	 0.3811956363971122 					 0.3966400833756608 
Iteration 38 	 0.3811956363971122 					 0.3966400833756608 
Iteration 39 	 0.3811956363971122 					 0.3966400833756608 
Iteration 40 	 0.3811956363971122 					 0.3966400833756608 
Iteration 41 	 0.3811956363971122 					 0.3966400833756608 
Iteration 42 	 0.3811956363971122 					 0.3966400833756608 
Iteration 43 	 0.3811956363971122 					 0.3966400833756608 
Iteration 44 	 0.3811956363971122 					 0.3966400833756608 
Iteration 45 	 0.3811956363971122 					 0.3966400833756608 
Iteration 46 	 0.3811956363971122 					 0.3966400833756608 
Iteration 47 	 0.3811956363971122 					 0.3966400833756608 
Iteration 48 	 0.3811956363971122 					 0.3966400833756608 
Iteration 49 	 0.3811956363971122 					 0.3966400833756608 


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Run Number - 10
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.3293970347629669 					 0.3293970347629669 
Iteration 1 	 0.3797996708314739 					 0.3797996708314739 
Iteration 2 	 0.3816465343018143 					 0.3816465343018143 
Iteration 3 	 0.38643483026658854 					 0.38643483026658854 
Iteration 4 	 0.4116585475918575 					 0.4116585475918575 
Iteration 5 	 0.420685501722192 					 0.420685501722192 
Iteration 6 	 0.4269948348449313 					 0.4269948348449313 
Iteration 7 	 0.43611637675033177 					 0.43611637675033177 
Iteration 8 	 0.43611637675033177 					 0.43611637675033177 
Iteration 9 	 0.4371917306946291 					 0.4371917306946291 
Iteration 10 	 0.4371917306946291 					 0.4371917306946291 
Iteration 11 	 0.4371917306946291 					 0.4371917306946291 
Iteration 12 	 0.4371917306946291 					 0.4371917306946291 
Iteration 13 	 0.4371917306946291 					 0.4371917306946291 
Iteration 14 	 0.4371917306946291 					 0.4371917306946291 
Iteration 15 	 0.4371917306946291 					 0.4371917306946291 
Iteration 16 	 0.4371917306946291 					 0.4371917306946291 
Iteration 17 	 0.4371917306946291 					 0.4371917306946291 
Iteration 18 	 0.4371917306946291 					 0.4371917306946291 
Iteration 19 	 0.4371917306946291 					 0.4371917306946291 
Iteration 20 	 0.4371917306946291 					 0.4371917306946291 
Iteration 21 	 0.4371917306946291 					 0.4371917306946291 
Iteration 22 	 0.4371917306946291 					 0.4371917306946291 
Iteration 23 	 0.4371917306946291 					 0.4371917306946291 
Iteration 24 	 0.4371917306946291 					 0.4371917306946291 
Iteration 25 	 0.4371917306946291 					 0.4371917306946291 
Iteration 26 	 0.4371917306946291 					 0.4371917306946291 
Iteration 27 	 0.4371917306946291 					 0.4371917306946291 
Iteration 28 	 0.4371917306946291 					 0.4371917306946291 
Iteration 29 	 0.4371917306946291 					 0.4371917306946291 
Iteration 30 	 0.4371917306946291 					 0.4371917306946291 
Iteration 31 	 0.4371917306946291 					 0.4371917306946291 
Iteration 32 	 0.4371917306946291 					 0.4371917306946291 
Iteration 33 	 0.4371917306946291 					 0.4371917306946291 
Iteration 34 	 0.4371917306946291 					 0.4371917306946291 
Iteration 35 	 0.4371917306946291 					 0.4371917306946291 
Iteration 36 	 0.4371917306946291 					 0.4371917306946291 
Iteration 37 	 0.4371917306946291 					 0.4371917306946291 
Iteration 38 	 0.4371917306946291 					 0.4371917306946291 
Iteration 39 	 0.4371917306946291 					 0.4371917306946291 
Iteration 40 	 0.4371917306946291 					 0.4371917306946291 
Iteration 41 	 0.4371917306946291 					 0.4371917306946291 
Iteration 42 	 0.4371917306946291 					 0.4371917306946291 
Iteration 43 	 0.4371917306946291 					 0.4371917306946291 
Iteration 44 	 0.4371917306946291 					 0.4371917306946291 
Iteration 45 	 0.4371917306946291 					 0.4371917306946291 
Iteration 46 	 0.4371917306946291 					 0.4371917306946291 
Iteration 47 	 0.4371917306946291 					 0.4371917306946291 
Iteration 48 	 0.4371917306946291 					 0.4371917306946291 
Iteration 49 	 0.4371917306946291 					 0.4371917306946291 


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Run Number - 11
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.38266661522265055 					 0.38266661522265055 
Iteration 1 	 0.3813810247544 					 0.38266661522265055 
Iteration 2 	 0.43372377355205455 					 0.43372377355205455 
Iteration 3 	 0.4440933876447244 					 0.4440933876447244 
Iteration 4 	 0.44341899584180106 					 0.4440933876447244 
Iteration 5 	 0.43734190431576725 					 0.4440933876447244 
Iteration 6 	 0.4069059647079589 					 0.4440933876447244 
Iteration 7 	 0.39239392485200797 					 0.4440933876447244 
Iteration 8 	 0.39239392485200797 					 0.4440933876447244 
Iteration 9 	 0.42718320533271803 					 0.4440933876447244 
Iteration 10 	 0.44888100231626954 					 0.44888100231626954 
Iteration 11 	 0.44888100231626954 					 0.44888100231626954 
Iteration 12 	 0.44888100231626954 					 0.44888100231626954 
Iteration 13 	 0.4501693759938368 					 0.4501693759938368 
Iteration 14 	 0.45013147433454037 					 0.4501693759938368 
Iteration 15 	 0.4524014090439429 					 0.4524014090439429 
Iteration 16 	 0.4504184438615736 					 0.4524014090439429 
Iteration 17 	 0.45013147433454037 					 0.4524014090439429 
Iteration 18 	 0.4501693759938368 					 0.4524014090439429 
Iteration 19 	 0.4501693759938368 					 0.4524014090439429 
Iteration 20 	 0.4501693759938368 					 0.4524014090439429 
Iteration 21 	 0.4501693759938368 					 0.4524014090439429 
Iteration 22 	 0.4501693759938368 					 0.4524014090439429 
Iteration 23 	 0.4501693759938368 					 0.4524014090439429 
Iteration 24 	 0.4501693759938368 					 0.4524014090439429 
Iteration 25 	 0.4501693759938368 					 0.4524014090439429 
Iteration 26 	 0.4501693759938368 					 0.4524014090439429 
Iteration 27 	 0.4501693759938368 					 0.4524014090439429 
Iteration 28 	 0.4501693759938368 					 0.4524014090439429 
Iteration 29 	 0.4501693759938368 					 0.4524014090439429 
Iteration 30 	 0.4501693759938368 					 0.4524014090439429 
Iteration 31 	 0.4501693759938368 					 0.4524014090439429 
Iteration 32 	 0.4501693759938368 					 0.4524014090439429 
Iteration 33 	 0.4501693759938368 					 0.4524014090439429 
Iteration 34 	 0.4501693759938368 					 0.4524014090439429 
Iteration 35 	 0.4501693759938368 					 0.4524014090439429 
Iteration 36 	 0.4501693759938368 					 0.4524014090439429 
Iteration 37 	 0.4501693759938368 					 0.4524014090439429 
Iteration 38 	 0.4501693759938368 					 0.4524014090439429 
Iteration 39 	 0.4501693759938368 					 0.4524014090439429 
Iteration 40 	 0.4501693759938368 					 0.4524014090439429 
Iteration 41 	 0.4501693759938368 					 0.4524014090439429 
Iteration 42 	 0.4501693759938368 					 0.4524014090439429 
Iteration 43 	 0.4501693759938368 					 0.4524014090439429 
Iteration 44 	 0.4501693759938368 					 0.4524014090439429 
Iteration 45 	 0.4501693759938368 					 0.4524014090439429 
Iteration 46 	 0.4501693759938368 					 0.4524014090439429 
Iteration 47 	 0.4501693759938368 					 0.4524014090439429 
Iteration 48 	 0.4501693759938368 					 0.4524014090439429 
Iteration 49 	 0.4501693759938368 					 0.4524014090439429 


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Run Number - 12
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.39772817031523156 					 0.39772817031523156 
Iteration 1 	 0.4308085379287222 					 0.4308085379287222 
Iteration 2 	 0.39084724667645687 					 0.4308085379287222 
Iteration 3 	 0.39720989163551196 					 0.4308085379287222 
Iteration 4 	 0.4050372262585692 					 0.4308085379287222 
Iteration 5 	 0.39722010509406214 					 0.4308085379287222 
Iteration 6 	 0.40495014512090827 					 0.4308085379287222 
Iteration 7 	 0.43837242678460475 					 0.43837242678460475 
Iteration 8 	 0.43837242678460475 					 0.43837242678460475 
Iteration 9 	 0.43837242678460475 					 0.43837242678460475 
Iteration 10 	 0.45093482311161803 					 0.45093482311161803 
Iteration 11 	 0.4412912870270086 					 0.45093482311161803 
Iteration 12 	 0.4412912870270086 					 0.45093482311161803 
Iteration 13 	 0.4508065323157856 					 0.45093482311161803 
Iteration 14 	 0.4656925030713467 					 0.4656925030713467 
Iteration 15 	 0.4656925030713467 					 0.4656925030713467 
Iteration 16 	 0.4656925030713467 					 0.4656925030713467 
Iteration 17 	 0.4656925030713467 					 0.4656925030713467 
Iteration 18 	 0.4656925030713467 					 0.4656925030713467 
Iteration 19 	 0.4656925030713467 					 0.4656925030713467 
Iteration 20 	 0.4656925030713467 					 0.4656925030713467 
Iteration 21 	 0.4656925030713467 					 0.4656925030713467 
Iteration 22 	 0.4656925030713467 					 0.4656925030713467 
Iteration 23 	 0.4656925030713467 					 0.4656925030713467 
Iteration 24 	 0.4656925030713467 					 0.4656925030713467 
Iteration 25 	 0.4656925030713467 					 0.4656925030713467 
Iteration 26 	 0.4430243727874738 					 0.4656925030713467 
Iteration 27 	 0.4430243727874738 					 0.4656925030713467 
Iteration 28 	 0.4430243727874738 					 0.4656925030713467 
Iteration 29 	 0.4430243727874738 					 0.4656925030713467 
Iteration 30 	 0.4430243727874738 					 0.4656925030713467 
Iteration 31 	 0.4430243727874738 					 0.4656925030713467 
Iteration 32 	 0.4430243727874738 					 0.4656925030713467 
Iteration 33 	 0.4430243727874738 					 0.4656925030713467 
Iteration 34 	 0.4430243727874738 					 0.4656925030713467 
Iteration 35 	 0.4430243727874738 					 0.4656925030713467 
Iteration 36 	 0.4430243727874738 					 0.4656925030713467 
Iteration 37 	 0.4430243727874738 					 0.4656925030713467 
Iteration 38 	 0.4430243727874738 					 0.4656925030713467 
Iteration 39 	 0.4430243727874738 					 0.4656925030713467 
Iteration 40 	 0.4430243727874738 					 0.4656925030713467 
Iteration 41 	 0.4430243727874738 					 0.4656925030713467 
Iteration 42 	 0.4430243727874738 					 0.4656925030713467 
Iteration 43 	 0.4430243727874738 					 0.4656925030713467 
Iteration 44 	 0.4430243727874738 					 0.4656925030713467 
Iteration 45 	 0.4430243727874738 					 0.4656925030713467 
Iteration 46 	 0.4430243727874738 					 0.4656925030713467 
Iteration 47 	 0.4430243727874738 					 0.4656925030713467 
Iteration 48 	 0.4430243727874738 					 0.4656925030713467 
Iteration 49 	 0.4430243727874738 					 0.4656925030713467 


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Run Number - 13
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.42931960537209274 					 0.42931960537209274 
Iteration 1 	 0.40995207306330145 					 0.42931960537209274 
Iteration 2 	 0.39774759875002663 					 0.42931960537209274 
Iteration 3 	 0.40843465766192644 					 0.42931960537209274 
Iteration 4 	 0.42484739787480974 					 0.42931960537209274 
Iteration 5 	 0.39707353517010063 					 0.42931960537209274 
Iteration 6 	 0.4137169383016799 					 0.42931960537209274 
Iteration 7 	 0.41280261762192233 					 0.42931960537209274 
Iteration 8 	 0.4163032910810245 					 0.42931960537209274 
Iteration 9 	 0.4206679682686401 					 0.42931960537209274 
Iteration 10 	 0.41804579740671777 					 0.42931960537209274 
Iteration 11 	 0.41890561547897764 					 0.42931960537209274 
Iteration 12 	 0.42430557584440687 					 0.42931960537209274 
Iteration 13 	 0.4314478670754234 					 0.4314478670754234 
Iteration 14 	 0.4314478670754234 					 0.4314478670754234 
Iteration 15 	 0.4271868705812919 					 0.4314478670754234 
Iteration 16 	 0.4271868705812919 					 0.4314478670754234 
Iteration 17 	 0.4271868705812919 					 0.4314478670754234 
Iteration 18 	 0.4271868705812919 					 0.4314478670754234 
Iteration 19 	 0.4271868705812919 					 0.4314478670754234 
Iteration 20 	 0.4271868705812919 					 0.4314478670754234 
Iteration 21 	 0.4271868705812919 					 0.4314478670754234 
Iteration 22 	 0.4271868705812919 					 0.4314478670754234 
Iteration 23 	 0.4271868705812919 					 0.4314478670754234 
Iteration 24 	 0.4271868705812919 					 0.4314478670754234 
Iteration 25 	 0.4271868705812919 					 0.4314478670754234 
Iteration 26 	 0.4271868705812919 					 0.4314478670754234 
Iteration 27 	 0.4271868705812919 					 0.4314478670754234 
Iteration 28 	 0.4271868705812919 					 0.4314478670754234 
Iteration 29 	 0.4271868705812919 					 0.4314478670754234 
Iteration 30 	 0.4271868705812919 					 0.4314478670754234 
Iteration 31 	 0.4271868705812919 					 0.4314478670754234 
Iteration 32 	 0.4271868705812919 					 0.4314478670754234 
Iteration 33 	 0.4271868705812919 					 0.4314478670754234 
Iteration 34 	 0.4271868705812919 					 0.4314478670754234 
Iteration 35 	 0.4271868705812919 					 0.4314478670754234 
Iteration 36 	 0.4271868705812919 					 0.4314478670754234 
Iteration 37 	 0.4271868705812919 					 0.4314478670754234 
Iteration 38 	 0.4271868705812919 					 0.4314478670754234 
Iteration 39 	 0.4271868705812919 					 0.4314478670754234 
Iteration 40 	 0.4271868705812919 					 0.4314478670754234 
Iteration 41 	 0.4271868705812919 					 0.4314478670754234 
Iteration 42 	 0.4271868705812919 					 0.4314478670754234 
Iteration 43 	 0.4271868705812919 					 0.4314478670754234 
Iteration 44 	 0.4271868705812919 					 0.4314478670754234 
Iteration 45 	 0.4271868705812919 					 0.4314478670754234 
Iteration 46 	 0.4271868705812919 					 0.4314478670754234 
Iteration 47 	 0.4271868705812919 					 0.4314478670754234 
Iteration 48 	 0.4271868705812919 					 0.4314478670754234 
Iteration 49 	 0.4271868705812919 					 0.4314478670754234 


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Run Number - 14
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4068093270355667 					 0.4068093270355667 
Iteration 1 	 0.4180930409060797 					 0.4180930409060797 
Iteration 2 	 0.4209074016438096 					 0.4209074016438096 
Iteration 3 	 0.4634309785219297 					 0.4634309785219297 
Iteration 4 	 0.4249193216486929 					 0.4634309785219297 
Iteration 5 	 0.45240387211148547 					 0.4634309785219297 
Iteration 6 	 0.45982143822015165 					 0.4634309785219297 
Iteration 7 	 0.45982143822015165 					 0.4634309785219297 
Iteration 8 	 0.45726281907884725 					 0.4634309785219297 
Iteration 9 	 0.45726281907884725 					 0.4634309785219297 
Iteration 10 	 0.46538520016773854 					 0.46538520016773854 
Iteration 11 	 0.46538520016773854 					 0.46538520016773854 
Iteration 12 	 0.46538520016773854 					 0.46538520016773854 
Iteration 13 	 0.46538520016773854 					 0.46538520016773854 
Iteration 14 	 0.46538520016773854 					 0.46538520016773854 
Iteration 15 	 0.46538520016773854 					 0.46538520016773854 
Iteration 16 	 0.46538520016773854 					 0.46538520016773854 
Iteration 17 	 0.46538520016773854 					 0.46538520016773854 
Iteration 18 	 0.46538520016773854 					 0.46538520016773854 
Iteration 19 	 0.46538520016773854 					 0.46538520016773854 
Iteration 20 	 0.46538520016773854 					 0.46538520016773854 
Iteration 21 	 0.46538520016773854 					 0.46538520016773854 
Iteration 22 	 0.46538520016773854 					 0.46538520016773854 
Iteration 23 	 0.46538520016773854 					 0.46538520016773854 
Iteration 24 	 0.46538520016773854 					 0.46538520016773854 
Iteration 25 	 0.46538520016773854 					 0.46538520016773854 
Iteration 26 	 0.46538520016773854 					 0.46538520016773854 
Iteration 27 	 0.46538520016773854 					 0.46538520016773854 
Iteration 28 	 0.46538520016773854 					 0.46538520016773854 
Iteration 29 	 0.46538520016773854 					 0.46538520016773854 
Iteration 30 	 0.46538520016773854 					 0.46538520016773854 
Iteration 31 	 0.46538520016773854 					 0.46538520016773854 
Iteration 32 	 0.46538520016773854 					 0.46538520016773854 
Iteration 33 	 0.46538520016773854 					 0.46538520016773854 
Iteration 34 	 0.46538520016773854 					 0.46538520016773854 
Iteration 35 	 0.46538520016773854 					 0.46538520016773854 
Iteration 36 	 0.46538520016773854 					 0.46538520016773854 
Iteration 37 	 0.46538520016773854 					 0.46538520016773854 
Iteration 38 	 0.46538520016773854 					 0.46538520016773854 
Iteration 39 	 0.46538520016773854 					 0.46538520016773854 
Iteration 40 	 0.46538520016773854 					 0.46538520016773854 
Iteration 41 	 0.46538520016773854 					 0.46538520016773854 
Iteration 42 	 0.46538520016773854 					 0.46538520016773854 
Iteration 43 	 0.46538520016773854 					 0.46538520016773854 
Iteration 44 	 0.46538520016773854 					 0.46538520016773854 
Iteration 45 	 0.46538520016773854 					 0.46538520016773854 
Iteration 46 	 0.46538520016773854 					 0.46538520016773854 
Iteration 47 	 0.46538520016773854 					 0.46538520016773854 
Iteration 48 	 0.46538520016773854 					 0.46538520016773854 
Iteration 49 	 0.46538520016773854 					 0.46538520016773854 


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Run Number - 15
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.38695909914953 					 0.38695909914953 
Iteration 1 	 0.3345320166867807 					 0.38695909914953 
Iteration 2 	 0.38913258314399357 					 0.38913258314399357 
Iteration 3 	 0.38913258314399357 					 0.38913258314399357 
Iteration 4 	 0.38062005199491356 					 0.38913258314399357 
Iteration 5 	 0.37267229338722907 					 0.38913258314399357 
Iteration 6 	 0.38862103431087824 					 0.38913258314399357 
Iteration 7 	 0.3744830318345619 					 0.38913258314399357 
Iteration 8 	 0.38862103431087824 					 0.38913258314399357 
Iteration 9 	 0.3658005647989233 					 0.38913258314399357 
Iteration 10 	 0.3658005647989233 					 0.38913258314399357 
Iteration 11 	 0.3658005647989233 					 0.38913258314399357 
Iteration 12 	 0.3658005647989233 					 0.38913258314399357 
Iteration 13 	 0.36777485059160636 					 0.38913258314399357 
Iteration 14 	 0.3793591117905838 					 0.38913258314399357 
Iteration 15 	 0.3596672691591023 					 0.38913258314399357 
Iteration 16 	 0.35400657161691496 					 0.38913258314399357 
Iteration 17 	 0.35400657161691496 					 0.38913258314399357 
Iteration 18 	 0.35400657161691496 					 0.38913258314399357 
Iteration 19 	 0.35400657161691496 					 0.38913258314399357 
Iteration 20 	 0.35400657161691496 					 0.38913258314399357 
Iteration 21 	 0.35400657161691496 					 0.38913258314399357 
Iteration 22 	 0.35400657161691496 					 0.38913258314399357 
Iteration 23 	 0.35400657161691496 					 0.38913258314399357 
Iteration 24 	 0.35400657161691496 					 0.38913258314399357 
Iteration 25 	 0.35400657161691496 					 0.38913258314399357 
Iteration 26 	 0.35400657161691496 					 0.38913258314399357 
Iteration 27 	 0.35400657161691496 					 0.38913258314399357 
Iteration 28 	 0.35400657161691496 					 0.38913258314399357 
Iteration 29 	 0.35400657161691496 					 0.38913258314399357 
Iteration 30 	 0.35400657161691496 					 0.38913258314399357 
Iteration 31 	 0.35400657161691496 					 0.38913258314399357 
Iteration 32 	 0.35400657161691496 					 0.38913258314399357 
Iteration 33 	 0.35400657161691496 					 0.38913258314399357 
Iteration 34 	 0.35400657161691496 					 0.38913258314399357 
Iteration 35 	 0.35400657161691496 					 0.38913258314399357 
Iteration 36 	 0.35400657161691496 					 0.38913258314399357 
Iteration 37 	 0.35400657161691496 					 0.38913258314399357 
Iteration 38 	 0.35400657161691496 					 0.38913258314399357 
Iteration 39 	 0.35400657161691496 					 0.38913258314399357 
Iteration 40 	 0.35400657161691496 					 0.38913258314399357 
Iteration 41 	 0.35400657161691496 					 0.38913258314399357 
Iteration 42 	 0.35400657161691496 					 0.38913258314399357 
Iteration 43 	 0.35400657161691496 					 0.38913258314399357 
Iteration 44 	 0.35400657161691496 					 0.38913258314399357 
Iteration 45 	 0.35400657161691496 					 0.38913258314399357 
Iteration 46 	 0.35400657161691496 					 0.38913258314399357 
Iteration 47 	 0.35400657161691496 					 0.38913258314399357 
Iteration 48 	 0.35400657161691496 					 0.38913258314399357 
Iteration 49 	 0.35400657161691496 					 0.38913258314399357 


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Run Number - 16
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.41437610646103906 					 0.41437610646103906 
Iteration 1 	 0.4228141518036241 					 0.4228141518036241 
Iteration 2 	 0.3907387232892884 					 0.4228141518036241 
Iteration 3 	 0.3809224216542342 					 0.4228141518036241 
Iteration 4 	 0.4126903037115459 					 0.4228141518036241 
Iteration 5 	 0.4126903037115459 					 0.4228141518036241 
Iteration 6 	 0.40950639773404196 					 0.4228141518036241 
Iteration 7 	 0.4177831769109899 					 0.4228141518036241 
Iteration 8 	 0.41777412472585923 					 0.4228141518036241 
Iteration 9 	 0.4056709405675615 					 0.4228141518036241 
Iteration 10 	 0.42167034005307136 					 0.4228141518036241 
Iteration 11 	 0.42167034005307136 					 0.4228141518036241 
Iteration 12 	 0.4354731464238484 					 0.4354731464238484 
Iteration 13 	 0.4354731464238484 					 0.4354731464238484 
Iteration 14 	 0.4354731464238484 					 0.4354731464238484 
Iteration 15 	 0.4354731464238484 					 0.4354731464238484 
Iteration 16 	 0.44319901227871006 					 0.44319901227871006 
Iteration 17 	 0.44319901227871006 					 0.44319901227871006 
Iteration 18 	 0.44319901227871006 					 0.44319901227871006 
Iteration 19 	 0.4354731464238484 					 0.44319901227871006 
Iteration 20 	 0.4354731464238484 					 0.44319901227871006 
Iteration 21 	 0.4354731464238484 					 0.44319901227871006 
Iteration 22 	 0.4354731464238484 					 0.44319901227871006 
Iteration 23 	 0.4354731464238484 					 0.44319901227871006 
Iteration 24 	 0.4354731464238484 					 0.44319901227871006 
Iteration 25 	 0.4354731464238484 					 0.44319901227871006 
Iteration 26 	 0.4354731464238484 					 0.44319901227871006 
Iteration 27 	 0.4354731464238484 					 0.44319901227871006 
Iteration 28 	 0.4354731464238484 					 0.44319901227871006 
Iteration 29 	 0.4354731464238484 					 0.44319901227871006 
Iteration 30 	 0.4354731464238484 					 0.44319901227871006 
Iteration 31 	 0.4354731464238484 					 0.44319901227871006 
Iteration 32 	 0.4354731464238484 					 0.44319901227871006 
Iteration 33 	 0.4354731464238484 					 0.44319901227871006 
Iteration 34 	 0.4354731464238484 					 0.44319901227871006 
Iteration 35 	 0.4354731464238484 					 0.44319901227871006 
Iteration 36 	 0.4354731464238484 					 0.44319901227871006 
Iteration 37 	 0.4354731464238484 					 0.44319901227871006 
Iteration 38 	 0.4354731464238484 					 0.44319901227871006 
Iteration 39 	 0.4354731464238484 					 0.44319901227871006 
Iteration 40 	 0.4354731464238484 					 0.44319901227871006 
Iteration 41 	 0.4354731464238484 					 0.44319901227871006 
Iteration 42 	 0.4354731464238484 					 0.44319901227871006 
Iteration 43 	 0.4354731464238484 					 0.44319901227871006 
Iteration 44 	 0.4354731464238484 					 0.44319901227871006 
Iteration 45 	 0.4354731464238484 					 0.44319901227871006 
Iteration 46 	 0.4354731464238484 					 0.44319901227871006 
Iteration 47 	 0.4354731464238484 					 0.44319901227871006 
Iteration 48 	 0.4354731464238484 					 0.44319901227871006 
Iteration 49 	 0.4354731464238484 					 0.44319901227871006 


 ----------------------------------------------------------------------------------------
Run Number - 17
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4350401175940261 					 0.4350401175940261 
Iteration 1 	 0.383363131064416 					 0.4350401175940261 
Iteration 2 	 0.40061104644674406 					 0.4350401175940261 
Iteration 3 	 0.42752117897669434 					 0.4350401175940261 
Iteration 4 	 0.4318807810139274 					 0.4350401175940261 
Iteration 5 	 0.4353867845678199 					 0.4353867845678199 
Iteration 6 	 0.44780140885623987 					 0.44780140885623987 
Iteration 7 	 0.45211097793961075 					 0.45211097793961075 
Iteration 8 	 0.45219350077612286 					 0.45219350077612286 
Iteration 9 	 0.44908418260962535 					 0.45219350077612286 
Iteration 10 	 0.44908418260962535 					 0.45219350077612286 
Iteration 11 	 0.44972350160981944 					 0.45219350077612286 
Iteration 12 	 0.44972350160981944 					 0.45219350077612286 
Iteration 13 	 0.44972350160981944 					 0.45219350077612286 
Iteration 14 	 0.44972350160981944 					 0.45219350077612286 
Iteration 15 	 0.44972350160981944 					 0.45219350077612286 
Iteration 16 	 0.44972350160981944 					 0.45219350077612286 
Iteration 17 	 0.44972350160981944 					 0.45219350077612286 
Iteration 18 	 0.44972350160981944 					 0.45219350077612286 
Iteration 19 	 0.44972350160981944 					 0.45219350077612286 
Iteration 20 	 0.44972350160981944 					 0.45219350077612286 
Iteration 21 	 0.44972350160981944 					 0.45219350077612286 
Iteration 22 	 0.44972350160981944 					 0.45219350077612286 
Iteration 23 	 0.44972350160981944 					 0.45219350077612286 
Iteration 24 	 0.44972350160981944 					 0.45219350077612286 
Iteration 25 	 0.44972350160981944 					 0.45219350077612286 
Iteration 26 	 0.44972350160981944 					 0.45219350077612286 
Iteration 27 	 0.44972350160981944 					 0.45219350077612286 
Iteration 28 	 0.44972350160981944 					 0.45219350077612286 
Iteration 29 	 0.44972350160981944 					 0.45219350077612286 
Iteration 30 	 0.44972350160981944 					 0.45219350077612286 
Iteration 31 	 0.44972350160981944 					 0.45219350077612286 
Iteration 32 	 0.44972350160981944 					 0.45219350077612286 
Iteration 33 	 0.44972350160981944 					 0.45219350077612286 
Iteration 34 	 0.44972350160981944 					 0.45219350077612286 
Iteration 35 	 0.44972350160981944 					 0.45219350077612286 
Iteration 36 	 0.44972350160981944 					 0.45219350077612286 
Iteration 37 	 0.44972350160981944 					 0.45219350077612286 
Iteration 38 	 0.44972350160981944 					 0.45219350077612286 
Iteration 39 	 0.44972350160981944 					 0.45219350077612286 
Iteration 40 	 0.44972350160981944 					 0.45219350077612286 
Iteration 41 	 0.44972350160981944 					 0.45219350077612286 
Iteration 42 	 0.44972350160981944 					 0.45219350077612286 
Iteration 43 	 0.44972350160981944 					 0.45219350077612286 
Iteration 44 	 0.44972350160981944 					 0.45219350077612286 
Iteration 45 	 0.44972350160981944 					 0.45219350077612286 
Iteration 46 	 0.44972350160981944 					 0.45219350077612286 
Iteration 47 	 0.44972350160981944 					 0.45219350077612286 
Iteration 48 	 0.44972350160981944 					 0.45219350077612286 
Iteration 49 	 0.44972350160981944 					 0.45219350077612286 


 ----------------------------------------------------------------------------------------
Run Number - 18
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.41320238682146504 					 0.41320238682146504 
Iteration 1 	 0.3813772407597441 					 0.41320238682146504 
Iteration 2 	 0.4411411490865095 					 0.4411411490865095 
Iteration 3 	 0.3850234933726432 					 0.4411411490865095 
Iteration 4 	 0.4526006664269601 					 0.4526006664269601 
Iteration 5 	 0.3945030139894866 					 0.4526006664269601 
Iteration 6 	 0.36500164383593425 					 0.4526006664269601 
Iteration 7 	 0.36500164383593425 					 0.4526006664269601 
Iteration 8 	 0.39030157813142025 					 0.4526006664269601 
Iteration 9 	 0.3831016403933059 					 0.4526006664269601 
Iteration 10 	 0.3831016403933059 					 0.4526006664269601 
Iteration 11 	 0.3831016403933059 					 0.4526006664269601 
Iteration 12 	 0.3831016403933059 					 0.4526006664269601 
Iteration 13 	 0.36254565600937155 					 0.4526006664269601 
Iteration 14 	 0.36254565600937155 					 0.4526006664269601 
Iteration 15 	 0.36254565600937155 					 0.4526006664269601 
Iteration 16 	 0.36254565600937155 					 0.4526006664269601 
Iteration 17 	 0.36254565600937155 					 0.4526006664269601 
Iteration 18 	 0.36254565600937155 					 0.4526006664269601 
Iteration 19 	 0.36254565600937155 					 0.4526006664269601 
Iteration 20 	 0.36254565600937155 					 0.4526006664269601 
Iteration 21 	 0.36254565600937155 					 0.4526006664269601 
Iteration 22 	 0.36254565600937155 					 0.4526006664269601 
Iteration 23 	 0.36254565600937155 					 0.4526006664269601 
Iteration 24 	 0.36254565600937155 					 0.4526006664269601 
Iteration 25 	 0.36254565600937155 					 0.4526006664269601 
Iteration 26 	 0.36254565600937155 					 0.4526006664269601 
Iteration 27 	 0.36254565600937155 					 0.4526006664269601 
Iteration 28 	 0.36254565600937155 					 0.4526006664269601 
Iteration 29 	 0.36254565600937155 					 0.4526006664269601 
Iteration 30 	 0.36254565600937155 					 0.4526006664269601 
Iteration 31 	 0.36254565600937155 					 0.4526006664269601 
Iteration 32 	 0.36254565600937155 					 0.4526006664269601 
Iteration 33 	 0.36254565600937155 					 0.4526006664269601 
Iteration 34 	 0.36254565600937155 					 0.4526006664269601 
Iteration 35 	 0.36254565600937155 					 0.4526006664269601 
Iteration 36 	 0.36254565600937155 					 0.4526006664269601 
Iteration 37 	 0.36254565600937155 					 0.4526006664269601 
Iteration 38 	 0.36254565600937155 					 0.4526006664269601 
Iteration 39 	 0.36254565600937155 					 0.4526006664269601 
Iteration 40 	 0.36254565600937155 					 0.4526006664269601 
Iteration 41 	 0.36254565600937155 					 0.4526006664269601 
Iteration 42 	 0.36254565600937155 					 0.4526006664269601 
Iteration 43 	 0.36254565600937155 					 0.4526006664269601 
Iteration 44 	 0.36254565600937155 					 0.4526006664269601 
Iteration 45 	 0.36254565600937155 					 0.4526006664269601 
Iteration 46 	 0.36254565600937155 					 0.4526006664269601 
Iteration 47 	 0.36254565600937155 					 0.4526006664269601 
Iteration 48 	 0.36254565600937155 					 0.4526006664269601 
Iteration 49 	 0.36254565600937155 					 0.4526006664269601 


 ----------------------------------------------------------------------------------------
Run Number - 19
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.37944082226582254 					 0.37944082226582254 
Iteration 1 	 0.39504404897300505 					 0.39504404897300505 
Iteration 2 	 0.37263825925002136 					 0.39504404897300505 
Iteration 3 	 0.3815662324683132 					 0.39504404897300505 
Iteration 4 	 0.38020160215078125 					 0.39504404897300505 
Iteration 5 	 0.3711194232440497 					 0.39504404897300505 
Iteration 6 	 0.4057756161751393 					 0.4057756161751393 
Iteration 7 	 0.39795678581242017 					 0.4057756161751393 
Iteration 8 	 0.4108888432440554 					 0.4108888432440554 
Iteration 9 	 0.4185458490858668 					 0.4185458490858668 
Iteration 10 	 0.4163626637707462 					 0.4185458490858668 
Iteration 11 	 0.4163626637707462 					 0.4185458490858668 
Iteration 12 	 0.4163626637707462 					 0.4185458490858668 
Iteration 13 	 0.4163626637707462 					 0.4185458490858668 
Iteration 14 	 0.4163626637707462 					 0.4185458490858668 
Iteration 15 	 0.4163626637707462 					 0.4185458490858668 
Iteration 16 	 0.4163626637707462 					 0.4185458490858668 
Iteration 17 	 0.4163626637707462 					 0.4185458490858668 
Iteration 18 	 0.4163626637707462 					 0.4185458490858668 
Iteration 19 	 0.4163626637707462 					 0.4185458490858668 
Iteration 20 	 0.4163626637707462 					 0.4185458490858668 
Iteration 21 	 0.4163626637707462 					 0.4185458490858668 
Iteration 22 	 0.4163626637707462 					 0.4185458490858668 
Iteration 23 	 0.4163626637707462 					 0.4185458490858668 
Iteration 24 	 0.4163626637707462 					 0.4185458490858668 
Iteration 25 	 0.4163626637707462 					 0.4185458490858668 
Iteration 26 	 0.4163626637707462 					 0.4185458490858668 
Iteration 27 	 0.4163626637707462 					 0.4185458490858668 
Iteration 28 	 0.4163626637707462 					 0.4185458490858668 
Iteration 29 	 0.4163626637707462 					 0.4185458490858668 
Iteration 30 	 0.4163626637707462 					 0.4185458490858668 
Iteration 31 	 0.4163626637707462 					 0.4185458490858668 
Iteration 32 	 0.4163626637707462 					 0.4185458490858668 
Iteration 33 	 0.4163626637707462 					 0.4185458490858668 
Iteration 34 	 0.4163626637707462 					 0.4185458490858668 
Iteration 35 	 0.4163626637707462 					 0.4185458490858668 
Iteration 36 	 0.4163626637707462 					 0.4185458490858668 
Iteration 37 	 0.4163626637707462 					 0.4185458490858668 
Iteration 38 	 0.4163626637707462 					 0.4185458490858668 
Iteration 39 	 0.4163626637707462 					 0.4185458490858668 
Iteration 40 	 0.4163626637707462 					 0.4185458490858668 
Iteration 41 	 0.4163626637707462 					 0.4185458490858668 
Iteration 42 	 0.4163626637707462 					 0.4185458490858668 
Iteration 43 	 0.4163626637707462 					 0.4185458490858668 
Iteration 44 	 0.4163626637707462 					 0.4185458490858668 
Iteration 45 	 0.4163626637707462 					 0.4185458490858668 
Iteration 46 	 0.4163626637707462 					 0.4185458490858668 
Iteration 47 	 0.4163626637707462 					 0.4185458490858668 
Iteration 48 	 0.4163626637707462 					 0.4185458490858668 
Iteration 49 	 0.4163626637707462 					 0.4185458490858668 


 ----------------------------------------------------------------------------------------
Run Number - 20
		 Best value of metric across iteration 	 Best value of metric across population  
Iteration 0 	 0.4072655628365437 					 0.4072655628365437 
Iteration 1 	 0.42510929738565845 					 0.42510929738565845 
Iteration 2 	 0.40885354370119126 					 0.42510929738565845 
Iteration 3 	 0.40885354370119126 					 0.42510929738565845 
Iteration 4 	 0.40885354370119126 					 0.42510929738565845 
Iteration 5 	 0.40885354370119126 					 0.42510929738565845 
Iteration 6 	 0.41779618617003467 					 0.42510929738565845 
Iteration 7 	 0.3956276381599082 					 0.42510929738565845 
Iteration 8 	 0.3956276381599082 					 0.42510929738565845 
Iteration 9 	 0.41887707862271295 					 0.42510929738565845 
Iteration 10 	 0.41887707862271295 					 0.42510929738565845 
Iteration 11 	 0.41887707862271295 					 0.42510929738565845 
Iteration 12 	 0.41887707862271295 					 0.42510929738565845 
Iteration 13 	 0.41887707862271295 					 0.42510929738565845 
Iteration 14 	 0.41887707862271295 					 0.42510929738565845 
Iteration 15 	 0.41887707862271295 					 0.42510929738565845 
Iteration 16 	 0.41887707862271295 					 0.42510929738565845 
Iteration 17 	 0.41887707862271295 					 0.42510929738565845 
Iteration 18 	 0.41887707862271295 					 0.42510929738565845 
Iteration 19 	 0.41887707862271295 					 0.42510929738565845 
Iteration 20 	 0.41887707862271295 					 0.42510929738565845 
Iteration 21 	 0.41887707862271295 					 0.42510929738565845 
Iteration 22 	 0.41887707862271295 					 0.42510929738565845 
Iteration 23 	 0.41887707862271295 					 0.42510929738565845 
Iteration 24 	 0.41887707862271295 					 0.42510929738565845 
Iteration 25 	 0.41887707862271295 					 0.42510929738565845 
Iteration 26 	 0.41887707862271295 					 0.42510929738565845 
Iteration 27 	 0.41887707862271295 					 0.42510929738565845 
Iteration 28 	 0.41887707862271295 					 0.42510929738565845 
Iteration 29 	 0.41887707862271295 					 0.42510929738565845 
Iteration 30 	 0.41887707862271295 					 0.42510929738565845 
Iteration 31 	 0.41887707862271295 					 0.42510929738565845 
Iteration 32 	 0.41887707862271295 					 0.42510929738565845 
Iteration 33 	 0.41887707862271295 					 0.42510929738565845 
Iteration 34 	 0.41887707862271295 					 0.42510929738565845 
Iteration 35 	 0.41887707862271295 					 0.42510929738565845 
Iteration 36 	 0.41887707862271295 					 0.42510929738565845 
Iteration 37 	 0.41887707862271295 					 0.42510929738565845 
Iteration 38 	 0.41887707862271295 					 0.42510929738565845 
Iteration 39 	 0.41887707862271295 					 0.42510929738565845 
Iteration 40 	 0.41887707862271295 					 0.42510929738565845 
Iteration 41 	 0.41887707862271295 					 0.42510929738565845 
Iteration 42 	 0.41887707862271295 					 0.42510929738565845 
Iteration 43 	 0.41887707862271295 					 0.42510929738565845 
Iteration 44 	 0.41887707862271295 					 0.42510929738565845 
Iteration 45 	 0.41887707862271295 					 0.42510929738565845 
Iteration 46 	 0.41887707862271295 					 0.42510929738565845 
Iteration 47 	 0.41887707862271295 					 0.42510929738565845 
Iteration 48 	 0.41887707862271295 					 0.42510929738565845 
Iteration 49 	 0.41887707862271295 					 0.42510929738565845


solutions_sigmoid['best_solution']

{'run_id': 3,
 'best_score': 0.4867647023511467,
 'num_features': 264,
 'selected_features': ['ALogP',
  'ALogp2',
  'AMR',
  'nAtom',
  'nH',
  'nC',
  'nN',
  'ATS3m',
  'ATS4m',
  'ATS8m',
  'ATS4v',
  'ATS6v',
  'ATS7v',
  'ATS8v',
  'ATS0e',
  'ATS1e',
  'ATS4e',
  'ATS6e',
  'ATS8e',
  'ATS1p',
  'ATS3p',
  'ATS5p',
  'ATS8p',
  'ATS0i',
  'ATS1i',
  'ATS3i',
  'ATS6i',
  'ATS7i',
  'ATS8i',
  'ATS0s',
  'ATS4s',
  'ATS6s',
  'ATS8s',
  'AATS2m',
  'AATS3m',
  'AATS4m',
  'AATS6m',
  'AATS2v',
  'AATS7v',
  'AATS0i',
  'AATS1i',
  'AATS4i',
  'AATS5i',
  'AATS6i',
  'AATS7i',
  'AATS8i',
  'AATS5s',
  'AATS6s',
  'AATS7s',
  'ATSC1m',
  'ATSC2m',
  'ATSC5m',
  'ATSC7m',
  'ATSC8m',
  'ATSC2v',
  'ATSC3e',
  'ATSC4e',
  'ATSC7e',
  'ATSC8e',
  'ATSC2p',
  'ATSC3p',
  'ATSC5p',
  'ATSC7p',
  'ATSC8p',
  'ATSC0i',
  'ATSC1i',
  'ATSC2i',
  'ATSC4i',
  'ATSC5i',
  'ATSC7i',
  'ATSC3s',
  'ATSC4s',
  'ATSC5s',
  'ATSC8s',
  'AATSC0m',
  'AATSC4m',
  'AATSC5m',
  'AATSC6m',
  'AATSC0v',
  'AATSC2v',
  'AATSC8v',
  'AATSC0s',
  'SpAD_DzZ',
  'SpMAD_DzZ',
  'EE_DzZ',
  'VE3_DzZ',
  'VR1_DzZ',
  'VR2_DzZ',
  'SpAbs_Dzm',
  'SpMax_Dzm',
  'SM1_Dzm',
  'VE3_Dzm',
  'VR2_Dzm',
  'SpAbs_Dzv',
  'SpDiam_Dzv',
  'SpMAD_Dzv',
  'EE_Dzv',
  'SM1_Dzv',
  'VR1_Dzv',
  'VR2_Dzv',
  'SpMax_Dze',
  'SpDiam_Dze',
  'SpMAD_Dze',
  'VE3_Dze',
  'VR2_Dze',
  'SM1_Dzp',
  'VR1_Dzp',
  'VR2_Dzp',
  'SpAbs_Dzi',
  'SpDiam_Dzi',
  'VE3_Dzi',
  'VR1_Dzi',
  'VR2_Dzi',
  'VR3_Dzi',
  'SpAbs_Dzs',
  'SpMax_Dzs',
  'VR1_Dzs',
  'BCUTp-1l',
  'BCUTp-1h',
  'nBondsS',
  'nBondsS2',
  'nBondsS3',
  'nBondsM',
  'C1SP2',
  'C2SP2',
  'C3SP2',
  'C1SP3',
  'C2SP3',
  'SP-7',
  'VP-1',
  'VP-6',
  'Sse',
  'Sare',
  'Sp',
  'CrippenLogP',
  'SpDiam_Dt',
  'SpAD_Dt',
  'SpMAD_Dt',
  'EE_Dt',
  'VE3_Dt',
  'VR1_Dt',
  'VR2_Dt',
  'ECCEN',
  'nHBd',
  'nwHBa',
  'nHBint2',
  'nHBint3',
  'nHBint5',
  'nHBint7',
  'nHBint9',
  'nHaaCH',
  'naaCH',
  'ndssC',
  'nssNH',
  'nsOH',
  'SHBd',
  'SHBint3',
  'SHBint5',
  'SHBint6',
  'SHBint7',
  'SHBint8',
  'SHBint10',
  'SHCsats',
  'SHCsatu',
  'SaasC',
  'SaaaC',
  'StN',
  'SsssN',
  'SdO',
  'SssO',
  'SsOm',
  'SsF',
  'SssS',
  'SddssS',
  'minHBint4',
  'minHBint7',
  'minHBint8',
  'minsCH3',
  'mindsCH',
  'minssNH',
  'mindsN',
  'minsssN',
  'minssO',
  'minaaO',
  'minsOm',
  'minddssS',
  'maxHBint2',
  'maxHBint3',
  'maxHBint4',
  'maxHBint6',
  'maxHBint8',
  'maxHBint9',
  'maxdsCH',
  'maxsNH2',
  'maxdNH',
  'maxdsN',
  'maxsssN',
  'maxsOH',
  'maxdO',
  'maxssO',
  'maxaaO',
  'maxsOm',
  'MAXDP2',
  'ETA_Beta',
  'ETA_Beta_s',
  'ETA_Beta_ns',
  'ETA_dBeta',
  'ETA_Beta_ns_d',
  'ETA_Eta_R_L',
  'fragC',
  'nHBAcc',
  'nHBAcc3',
  'nHBDon',
  'nHBDon_Lipinski',
  'TIC1',
  'TIC4',
  'MIC1',
  'MIC2',
  'MIC5',
  'ZMIC0',
  'ZMIC2',
  'ZMIC3',
  'ZMIC4',
  'Kier1',
  'Kier2',
  'nAtomLC',
  'nAtomP',
  'nAtomLAC',
  'MDEC-12',
  'MDEC-13',
  'MDEC-23',
  'MDEC-33',
  'MDEC-34',
  'MDEN-22',
  'MLFER_BO',
  'MPC4',
  'MPC5',
  'MPC6',
  'MPC7',
  'MPC8',
  'MPC9',
  'TPC',
  'piPC9',
  'piPC10',
  'R_TpiPCTPC',
  'nFG12Ring',
  'nT6Ring',
  'nHeteroRing',
  'n6HeteroRing',
  'nF10HeteroRing',
  'nFG12HeteroRing',
  'nRotB',
  'nRotBt',
  'LipinskiFailures',
  'topoDiameter',
  'GGI4',
  'SpMax_D',
  'SpAD_D',
  'VR1_D',
  'TWC',
  'SRW5',
  'SRW7',
  'AMW',
  'XLogP'],
 'plot': Figure({
     'data': [{'mode': 'markers',
               'name': 'objective_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.36955577186236105, 0.3800828275628093, 0.3807618344262117,
                           0.40940226709420446, 0.4023019161583719, 0.4023019161583719,
                           0.4428600634933584, 0.4420153148723352, 0.44460117190310056,
                           0.478837200382175, 0.47281759558847014, 0.47281759558847014,
                           0.47281759558847014, 0.47281759558847014, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467], dtype=object)},
              {'mode': 'lines+markers',
               'name': 'best_score',
               'type': 'scatter',
               'x': array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
                           18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                           36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], dtype=int64),
               'y': array([0.36955577186236105, 0.3800828275628093, 0.3807618344262117,
                           0.40940226709420446, 0.40940226709420446, 0.40940226709420446,
                           0.4428600634933584, 0.4428600634933584, 0.44460117190310056,
                           0.478837200382175, 0.478837200382175, 0.478837200382175,
                           0.478837200382175, 0.478837200382175, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467, 0.4867647023511467,
                           0.4867647023511467, 0.4867647023511467], dtype=object)}],
     'layout': {'template': '...',
                'title': {'text': 'Optimization History Plot'},
                'xaxis': {'title': {'text': 'Iteration'}},
                'yaxis': {'title': {'text': 'objective_score'}}}
 })}


solutions_sigmoid['best_solution']['plot']


### save and export selected features to pickle
results = [solutions_linear, solutions_rbf, solutions_poly]
# joblib.dump(results, 'Dataset Falcipain\selected_features_GA.pkl')

['Dataset Falcipain\\selected_features_GA.pkl']


# svr_model = make_pipeline(StandardScaler(), SVR(kernel='rbf'))
# solution_obj = features_select_GA(svr_model, X_train_fs, y_train_fs, X_valid, y_valid)

	nAcid	ALogP	ALogp2	AMR	apol	naAromAtom	nAromBond	nAtom	nHeavyAtom	nH	...	WTPT-1	WTPT-2	WTPT-3	WTPT-4	WTPT-5	WPATH	WPOL	XLogP	Zagreb	FP-2 pIC50 (uM)
0	0	-1.7616	3.103235	63.7293	78.280825	18	18	66	41	25	...	83.993479	2.048621	34.064095	18.736877	12.809614	5788.0	68.0	4.894	216.0	4.786748
1	0	-0.2864	0.082025	35.9367	51.005895	17	18	40	25	15	...	50.633970	2.025359	22.966476	5.077089	12.324973	1713.0	35.0	4.202	128.0	5.236572
2	0	-1.6982	2.883883	67.5532	68.066618	12	12	57	31	26	...	62.201948	2.006514	25.902949	12.501332	6.478960	3056.0	48.0	4.279	160.0	6.853872
3	0	-1.9096	3.646572	25.3604	59.650274	22	23	48	30	18	...	61.653743	2.055125	16.365920	10.101942	6.263978	2695.0	50.0	5.554	158.0	5.337242
4	0	-0.2266	0.051348	76.0728	60.954204	6	6	54	26	28	...	51.539400	1.982285	16.801571	5.118101	9.140872	1828.0	36.0	5.063	128.0	4.314258
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
201	0	-3.0982	9.598843	91.0329	100.488892	18	18	88	44	44	...	88.247274	2.005620	28.550281	13.040374	12.076740	8004.0	56.0	11.177	210.0	6.920819
202	0	-0.3931	0.154528	73.2009	80.554239	18	18	66	43	23	...	87.681842	2.039113	39.120294	18.734180	12.802907	6540.0	74.0	5.287	228.0	4.717831
203	0	-0.4597	0.211324	23.7925	39.802723	12	12	32	21	11	...	42.894845	2.042612	14.181190	10.716204	3.464986	952.0	33.0	4.315	110.0	4.292430
204	0	0.3782	0.143035	80.8866	96.319720	20	22	84	44	40	...	91.145467	2.071488	28.490904	9.714082	18.776823	8184.0	77.0	8.758	238.0	5.283997
205	0	-0.8986	0.807482	12.7875	33.345137	12	12	26	17	9	...	35.088264	2.064016	8.656029	5.132018	3.524012	468.0	28.0	3.909	92.0	4.292430

	nAcid	ALogP	ALogp2	AMR	apol	naAromAtom	nAromBond	nAtom	nHeavyAtom	nH	...	WTPT-1	WTPT-2	WTPT-3	WTPT-4	WTPT-5	WPATH	WPOL	XLogP	Zagreb	FP-2 pIC50 (uM)
0	0	-2.4530	6.017209	70.1618	78.000618	18	18	67	41	26	...	82.665017	2.016220	31.908282	31.908282	0.000000	6076.0	70.0	2.519	214.0	5.423659
1	0	-0.5409	0.292573	150.8291	107.252029	6	6	99	46	53	...	90.237619	1.961687	31.260021	15.819162	15.440859	9434.0	66.0	5.879	222.0	8.018181
2	0	0.4880	0.238144	84.5571	92.196927	16	17	81	42	39	...	87.941112	2.093836	27.912965	18.620374	9.292591	6991.0	86.0	8.780	242.0	6.537602
3	0	1.0195	1.039380	78.1138	88.191548	16	17	77	41	36	...	85.913699	2.095456	27.646474	15.819647	9.280255	6510.0	84.0	9.183	238.0	6.173925
4	0	0.7574	0.573655	19.4795	45.614309	16	17	36	23	13	...	46.973829	2.042340	10.439589	7.405732	3.033857	1342.0	34.0	7.620	118.0	4.718967
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
84	0	-1.2223	1.494017	32.4347	65.042239	21	22	54	31	23	...	63.750810	2.056478	17.386120	8.166102	9.220018	2885.0	43.0	6.894	158.0	4.527244
85	0	-1.1975	1.434006	51.3510	55.529446	10	11	48	26	22	...	51.793212	1.992047	25.825999	13.288478	9.027974	1928.0	37.0	3.265	126.0	4.272459
86	0	1.6302	2.657552	51.2062	60.343274	17	18	50	32	18	...	64.059996	2.001875	23.813396	14.104692	0.000000	3290.0	52.0	5.850	166.0	5.309804
87	0	-2.2931	5.258308	70.1726	82.286204	18	18	70	42	28	...	86.014892	2.047974	34.338321	21.520423	12.817898	6267.0	70.0	4.491	220.0	5.056011
88	0	0.1757	0.030870	29.9610	42.601895	12	13	34	19	15	...	38.146753	2.007724	10.588497	0.000000	8.206080	808.0	25.0	6.778	92.0	5.000000

	ALogP	ALogp2	AMR	apol	naAromAtom	nAromBond	nAtom	nHeavyAtom	nH	nC	...	MW	AMW	WTPT-1	WTPT-3	WTPT-4	WTPT-5	WPATH	WPOL	XLogP	Zagreb
0	-1.7616	3.103235	63.7293	78.280825	18	18	66	41	25	29	...	560.170727	8.487435	83.993479	34.064095	18.736877	12.809614	5788.0	68.0	4.894	216.0
1	-0.2864	0.082025	35.9367	51.005895	17	18	40	25	15	17	...	374.060424	9.351511	50.633970	22.966476	5.077089	12.324973	1713.0	35.0	4.202	128.0
2	-1.6982	2.883883	67.5532	68.066618	12	12	57	31	26	22	...	462.128314	8.107514	62.201948	25.902949	12.501332	6.478960	3056.0	48.0	4.279	160.0
3	-1.9096	3.646572	25.3604	59.650274	22	23	48	30	18	24	...	398.126657	8.294305	61.653743	16.365920	10.101942	6.263978	2695.0	50.0	5.554	158.0
4	-0.2266	0.051348	76.0728	60.954204	6	6	54	26	28	20	...	377.187005	6.984945	51.539400	16.801571	5.118101	9.140872	1828.0	36.0	5.063	128.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
201	-3.0982	9.598843	91.0329	100.488892	18	18	88	44	44	34	...	620.303242	7.048900	88.247274	28.550281	13.040374	12.076740	8004.0	56.0	11.177	210.0
202	-0.3931	0.154528	73.2009	80.554239	18	18	66	43	23	29	...	656.071818	9.940482	87.681842	39.120294	18.734180	12.802907	6540.0	74.0	5.287	228.0
203	-0.4597	0.211324	23.7925	39.802723	12	12	32	21	11	16	...	281.068808	8.783400	42.894845	14.181190	10.716204	3.464986	952.0	33.0	4.315	110.0
204	0.3782	0.143035	80.8866	96.319720	20	22	84	44	40	34	...	596.311104	7.098942	91.145467	28.490904	9.714082	18.776823	8184.0	77.0	8.758	238.0
205	-0.8986	0.807482	12.7875	33.345137	12	12	26	17	9	14	...	223.063329	8.579359	35.088264	8.656029	5.132018	3.524012	468.0	28.0	3.909	92.0

	ALogP	ALogp2	AMR	apol	naAromAtom	nAromBond	nAtom	nHeavyAtom	nH	nC	...	MW	AMW	WTPT-1	WTPT-3	WTPT-4	WTPT-5	WPATH	WPOL	XLogP	Zagreb
0	-0.667307	0.060116	0.023334	0.619897	0.913049	0.784631	0.545121	1.220854	0.031516	0.917177	...	1.040934	0.238029	1.266837	1.524384	1.479466	0.729893	0.899578	1.379152	-0.037628	1.330254
1	0.303730	-0.709409	-0.922499	-0.725249	0.718139	0.784631	-0.794791	-0.692572	-0.822722	-0.832253	...	-0.571242	1.003432	-0.700491	-0.028198	-0.899455	0.628256	-0.708953	-0.844105	-0.301112	-0.723821
2	-0.625575	0.004245	0.153468	0.116153	-0.256411	-0.301376	0.081305	0.024963	0.116939	-0.103324	...	0.191644	-0.098506	-0.018287	0.382621	0.393514	-0.597750	-0.178829	0.031723	-0.271793	0.023115
3	-0.764727	0.198508	-1.282429	-0.298925	1.692690	1.689636	-0.382510	-0.094626	-0.566450	0.188248	...	-0.362769	0.066954	-0.050616	-0.951631	-0.024352	-0.642836	-0.321327	0.166466	0.213671	-0.023568
4	0.343092	-0.717223	0.443405	-0.234618	-1.425871	-1.387382	-0.073300	-0.572983	0.287787	-0.394895	...	-0.544159	-1.092884	-0.647095	-0.890682	-0.892313	-0.039503	-0.663559	-0.776734	0.026719	-0.723821
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
201	-1.547112	1.714596	0.952525	1.715156	0.913049	0.784631	1.678892	1.579621	1.654566	1.646105	...	1.561830	-1.036232	1.517698	0.752989	0.487391	0.576197	1.774303	0.570695	2.354662	1.190203
202	0.233495	-0.690942	0.345670	0.732018	0.913049	0.784631	0.545121	1.460032	-0.139332	0.917177	...	1.871675	1.525145	1.484353	2.231758	1.478996	0.728487	1.196416	1.783381	0.112009	1.610355
203	0.189656	-0.676476	-1.335788	-1.277767	-0.256411	-0.301376	-1.207071	-1.170928	-1.164417	-0.978039	...	-1.376780	0.500197	-1.156895	-1.257280	0.082625	-1.229831	-1.009344	-0.978848	-0.258086	-1.143973
204	0.741196	-0.693869	0.607228	1.509540	1.302870	1.508635	1.472752	1.579621	1.312871	1.646105	...	1.353999	-0.991905	1.688615	0.744682	-0.091899	1.981316	1.845355	1.985495	1.433613	1.843773
205	-0.099245	-0.524630	-1.710308	-1.596243	-0.256411	-0.301376	-1.516282	-1.649285	-1.335264	-1.269610	...	-1.879251	0.319456	-1.617277	-2.030262	-0.889889	-1.217452	-1.200394	-1.315706	-0.412673	-1.564125

	ALogP	ALogp2	AMR	apol	naAromAtom	nAromBond	nAtom	nHeavyAtom	nH	nC	...	MW	AMW	WTPT-1	WTPT-3	WTPT-4	WTPT-5	WPATH	WPOL	XLogP	Zagreb
0	-1.122415	0.802327	0.242243	0.606078	0.913049	0.784631	0.596656	1.220854	0.116939	0.917177	...	1.092663	0.204769	1.188493	1.222781	3.773332	-1.956496	1.013261	1.513895	-0.941924	1.283571
1	0.136207	-0.655781	2.987497	2.048700	-1.425871	-1.387382	2.245778	1.818800	2.423380	1.791891	...	1.727252	-1.559139	1.635076	1.132088	0.971331	1.281709	2.338770	1.244410	0.337416	1.470305
2	0.813471	-0.669644	0.732142	1.306212	0.523229	0.603630	1.318147	1.340443	1.227448	1.500320	...	1.154526	-1.010828	1.499643	0.663827	1.459176	-0.007685	1.374440	2.591838	1.441990	1.937140
3	1.163326	-0.465564	0.512864	1.108675	0.523229	0.603630	1.112007	1.220854	0.971176	1.354534	...	1.050403	-0.823425	1.380079	0.626544	0.971415	-0.010272	1.184574	2.457096	1.595435	1.843773
4	0.990801	-0.584187	-1.482567	-0.991151	0.523229	0.603630	-1.000931	-0.931750	-0.993569	-0.540681	...	-1.186026	0.177546	-0.916343	-1.780738	-0.493910	-1.320246	-0.855399	-0.911477	1.000313	-0.957239
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
84	-0.312318	-0.349764	-1.041678	-0.033004	1.497780	1.508635	-0.073300	0.024963	-0.139332	0.334033	...	-0.232423	-0.502562	0.073055	-0.808903	-0.361488	-0.022905	-0.246328	-0.305134	0.723884	-0.023568
85	-0.295994	-0.365049	-0.397922	-0.502156	-0.646231	-0.482377	-0.382510	-0.572983	-0.224756	-0.832253	...	-0.527330	-0.283621	-0.632127	0.371856	0.530600	-0.063180	-0.624086	-0.709362	-0.657880	-0.770505
86	1.565314	-0.053403	-0.402850	-0.264747	0.718139	0.784631	-0.279440	0.144552	-0.566450	0.042462	...	0.225871	0.976928	0.091289	0.090288	0.672747	-1.956496	-0.086462	0.301209	0.326375	0.163166
87	-1.017162	0.609029	0.242611	0.817435	0.913049	0.784631	0.751261	1.340443	0.287787	1.062962	...	1.145057	-0.039478	1.386047	1.562749	1.964234	0.731630	1.088655	1.513895	-0.191073	1.423621
88	0.607903	-0.722439	-1.125862	-1.139717	-0.256411	-0.120375	-1.104001	-1.410107	-0.822722	-1.123824	...	-1.480471	-0.269332	-1.436907	-1.759906	-1.783656	-0.235545	-1.066186	-1.517820	0.679716	-1.564125

Statistical features selection¶

Using Variance Theresholds¶

Standarization Data¶

Metaheuristic features selection¶

Using Genetic Algorithm from ZOOFS Library ¶

ZOOFS is a Python library for performing feature selection using a variety of nature inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics based to Evolutionary. It's an easy to use, flexible and powerful tool to reduce your feature size.¶

ZOOFS Library and Dependencies¶

Performing GA-SVM Features Selection¶

Linear Kernel¶

RBF Kernel¶

Poly Kernel¶

Sigmoid Kernel¶

Export Genetic Features Selection Result¶

TEST¶

Statistical features selection¶

Using Variance Theresholds¶

Standarization Data¶

Metaheuristic features selection¶

Using Genetic Algorithm from ZOOFS Library¶

ZOOFS is a Python library for performing feature selection using a variety of nature inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics based to Evolutionary. It's an easy to use, flexible and powerful tool to reduce your feature size.¶

ZOOFS Library and Dependencies¶

Performing GA-SVM Features Selection¶

Linear Kernel¶

RBF Kernel¶

Poly Kernel¶

Sigmoid Kernel¶

Export Genetic Features Selection Result¶

TEST¶

Using Genetic Algorithm from ZOOFS Library ¶